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We are looking for a senior, hands-on DevOps and Backend Integration Engineer to lead the production deployment and integration of an existing application ecosystem.

The platform currently includes a Flutter mobile application, a Laravel backend and admin panel, Node.js/AdonisJS APIs, a Python recommendation service, Redis, MySQL, Nginx, and AWS S3.

This is not a greenfield development role. The primary objective is to audit the existing system, establish a reliable production infrastructure, integrate all services, migrate traffic safely, and complete the production launch.

Responsibilities

• Audit the existing Hostinger environment, source repositories, application dependencies, database, Redis configuration, and deployment process.

• Design a secure and maintainable production architecture for Laravel, Node.js/AdonisJS, Python, Redis, MySQL, Nginx, AWS S3, and the Flutter application.

• Provision and configure Linux production servers, runtimes, SSH access, environment variables, permissions, SSL, and basic server security.

• Deploy and configure the Laravel application, admin panel, APIs, scheduled tasks, queues, and database connectivity.

• Deploy the Node.js/AdonisJS services with a reliable build, startup, logging, and process-management setup.

• Build a Git-based CI/CD pipeline for staging and production, including secrets management, deployment validation, and basic rollback handling.

• Configure Nginx as a reverse proxy and route traffic between Laravel and Node.js services using API versions and endpoint rules.

• Install and integrate Redis for agreed caching, queue, or session-management requirements.

• Configure AWS S3, IAM permissions, secure file access, and photo-upload integration to replace local server storage.

• Integrate the existing Python recommendation service with the Node.js backend, including timeout, retry, error-handling, and service-health scenarios.

• Support controlled migration of API traffic from Laravel to Node.js while preserving existing API contracts.

• Verify Flutter API compatibility, production environment configuration, authentication flows, media uploads, and backend-related integration issues.

• Conduct end-to-end, regression, and smoke testing across Flutter, Nginx, Laravel, Node.js, Redis, Python, MySQL, and AWS S3.

• Perform production cutover, validation, troubleshooting, and technical handover.

• Deliver clear architecture, deployment, routing, environment, rollback, and operational documentation.

Required Experience

• 5+ years of professional backend, DevOps, infrastructure, or platform-engineering experience.

• Strong hands-on Linux server administration and production deployment experience.

• Proven experience deploying and operating Laravel/PHP and Node.js applications.

• Strong knowledge of Nginx reverse proxy configuration, SSL, upstream services, and API routing.

• Experience creating CI/CD pipelines using GitHub Actions, GitLab CI, Bitbucket Pipelines, or a comparable platform.

• Practical experience with AWS S3, IAM permissions, secure media uploads, and cloud-storage integration.

• Experience with Redis, MySQL, background workers, queues, scheduled jobs, and application caching.

• Experience integrating Python services or machine-learning/recommendation APIs with Node.js applications.

• Good understanding of REST APIs, API versioning, authentication, secrets management, logging, monitoring, backups, and rollback procedures.

• Ability to independently investigate an existing codebase and resolve production integration problems.

• Strong written English and the ability to produce clear technical documentation.

Nice to Have

• Experience with AdonisJS.

• Experience supporting Flutter applications and mobile backend integrations.

• Experience migrating applications from shared hosting or Hostinger to a production cloud server.

• Experience with Google Maps Platform or location-based application services.

• Docker experience is helpful, although Kubernetes is not required.

Expected Deliverables

• Documented production architecture.

• Fully configured production infrastructure.

• Working Laravel, Node.js/AdonisJS, Python, Redis, MySQL, Nginx, and AWS S3 integrations.

• Functional staging and production CI/CD workflows.

• Tested Laravel and Node.js coexistence with controlled API routing.

• Successful end-to-end production deployment.

• Rollback, deployment, configuration, and operational documentation.

Engagement Details

• Contract duration: approximately 4–5 weeks.

• Work arrangement: remote.

• Availability: candidates should be able to begin shortly and provide regular written progress updates.

• The current Node.js APIs and recommendation algorithm already exist. Major new product features, algorithm redesign, extensive Flutter feature development, and database redesign are outside the initial scope.

How to Apply

Please include:

1. Examples of Laravel and Node.js systems you have deployed to production.

2. Details of a CI/CD pipeline and Nginx routing setup you personally implemented.

3. Your experience integrating Redis, AWS S3, and Python services.

Job Title: Full Stack AI Engineer

Location: Remote/Hyderabad

Experience Level: 3-5

Salary Range: 12-18LPA

Application Link:https://beyond.ciltriq.com/apply/BUILD

Description:

Join a team building AI-powered systems that solve complex business problems and automate operational workflows across document processing, voice agents, enterprise integrations, workflow automation, and multi-agent systems.

Strong full-stack foundations: frontend state management, asynchronous user experiences and performance; backend API design, authentication, data modelling, databases, queues and distributed systems.

Strong coding ability in Python and JavaScript or TypeScript, with practical experience in modern frontend frameworks and backend services.

Requirements:

- Design and build complete systems: frontend applications, backend services, APIs, databases, data pipelines and integrations with customer systems.

- Build multi-agent workflows with clear agent responsibilities, tool access, shared state, context management, routing, handoffs and coordination across sequential and parallel tasks.

- Make agent execution dependable through durable state, checkpoints, retries, timeouts, idempotency, recovery and human approval or review where needed.

- Deliver document-processing pipelines, voice agents and retrieval-based AI applications, connecting model outputs to useful actions in real business workflows.

- Own quality in production: automated tests, AI evaluations, guardrails, observability, access controls, deployments, incident response and clear documentation.

- Choose where AI adds value and where deterministic software is the better fit. Balance accuracy, latency, cost, security and maintainability.

- Improve reusable engineering foundations, review code and help other engineers grow as the team expands.

- A solid understanding of tool calling, structured outputs, retrieval, context and memory management, model selection and evaluation.

- Practical cloud and deployment experience, including containers, CI/CD, secrets management, logging, monitoring and production debugging.

- Ability to reason from first principles, investigate failures across system boundaries and communicate technical decisions clearly to customers and teammates.

- Useful additional experience: Document AI and OCR, real-time voice systems, enterprise integrations, agent protocols such as MCP, and orchestration frameworks.

- Useful additional experience: Mentoring engineers or building reusable platforms.

About Us:

CLOUDSUFI, a Google Cloud Premier Partner, is a global leading provider of data-driven digital transformation across cloud-based enterprises. With a global presence and focus on Software & Platforms, Life sciences and Healthcare, Retail, CPG, financial services and supply chain, CLOUDSUFI is positioned to meet customers where they are in their data monetization journey.

Our Values

We are a passionate and empathetic team that prioritizes human values. Our purpose is to elevate the quality of lives for our family, customers, partners and the community.

Equal Opportunity Statement

CLOUDSUFI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified candidates receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation and national origin status. We provide equal opportunities in employment, advancement, and all other areas of our workplace. Please explore more at https://www.cloudsufi.com/

Role :

A Software Engineer who builds the tools this company runs on. You build agent loops, and the loops build the solutions. You work towards a Company Brain that anyone here can ask.3–5 years’ experience · Reports to the CFO · 

THE KEY SKILL

You build the agent loops that build the solutions. You will not write every automation by hand. You build the loops that

write them. Ship a prototype every week. You ship something every day.

You’ll be building a Company Brain with access control. One system that holds what the company knows about finance,delivery and people. Anyone can ask it a question. Each person sees only what they are cleared to see.

One hard filter. If you cannot write and debug production code, and have not done it before, please do not apply.

CORE RESPONSIBILITIES

• Work the backlog: You pick items off a live, ranked backlog. You learn each function by building inside it. There is no discovery phase. What you learn goes back into the backlog and changes what comes next.

• Build the product: You design, build and ship tools that people use every day. Reconciliation, MIS, the deal desk,quote to cash, or whatever the real bottleneck turns out to be. You choose the tools and frameworks.

• Wire the data: Connect the systems each team already uses, so that the same number means the same thing everywhere.

• Make it visible: You build live dashboards and alerts that leaders read on their own, instead of asking someone for a report.

• Keep it running: You own uptime and accuracy for everything you build. Anything that touches money or people needs a person in the loop.

THE STACK

• Build with: Python and TypeScript. You write production code. Frontier model APIs from Anthropic, OpenAI or Google, with tool calling and structured output. At least one agent framework. MCP to connect agents to internal systems.Postgres and pgvector, or something similar, for retrieval. You deploy on GCP, and you debug your own work.

• Work in agents daily: Claude Code, Cursor or something like them, as the way you write code every day. You should have a clear view on how to run the loop, and on when a person has to step in.

• Connect to: The systems we already run on for accounting, CRM, hiring and IT support, along with Google Workspace.Most of the work is getting them to agree with each other.

• Check what you ship: Anything that produces a number needs a way to catch it going quietly wrong. Test sets, regression checks, and alerts on the output as well as on the job.

WHAT GOOD LOOKS LIKE

• Something you built is running by week two, and someone is using it.

• By day 90, time spent on reconciliation or reporting is down by a number you can defend to the CFO.

• Every tool you ship has a named owner who is still using it 60 days later. That is the measure that counts.

• Leaders stop asking for numbers, because they can already see them.

• By the end of your first year, a first version of the Company Brain answers real questions about Finance, and each

person who asks sees only what they are cleared to see.

WHO THIS IS FOR

• You have built products: 3 to 5 years at a software product company, on a product with real users at scale. That means 100k+ monthly active users, or heavy daily use by a large enterprise customer base. You have owned code in production, in front of real users, long after it shipped.

• You ship alone: You are comfortable as the only engineer in the room, and the only person on call for what you built.

• You work out new ground fast: A domain you do not know is interesting to you. You start without waiting for a spec or an expert.

• You are fluent with agents: One person cannot cover a whole company by hand. You use agent loops heavily and youare good at it.

• You write and speak clearly: Half this job is pulling a process out of a finance or delivery lead and giving it back to them correctly. You work remotely, so this matters a great deal.

HOW WE WILL ASSESS

• A design problem: Live. We give you a function of the B2B company, and you design the system for it. We watch how you break down a domain you do not know, how you size it, and what you leave out on purpose.

• A build exercise: Live and screen-shared, on your own setup, with your own agents. You build the way you normally build. We watch how you run the loop, when you step in, and what you decide to skip.

• Your work and your questions: We talk about what you have shipped before. You ask us whatever you want.

Communication is not a separate round. All three sessions are live, and how clearly you explain your thinking is part of how we judge you.

WHERE IT LEADS

You report to the CEO and CFO from your first day. Your charter covers the whole company. Nothing sits between you and production. Very few engineering jobs offer all three at once, and that is why this one exists.

In 18 months you will know how this company really runs: the data, the money, and the gaps between teams. The rolethen changes shape to fit whatever the biggest open problem is by then.

At Nineleaps, we work on bleeding-edge technology with class-leading engineering practices on products that touch the lives of millions of users. We endeavor on doing things the right way, while also promoting a culture of excellence.

About the Role:

We are looking for a Data Analyst with strong analytical and problem-solving skills to transform complex data into meaningful, actionable business insights. The role involves working with large datasets, conducting deep-dive analysis, driving automation, and supporting data-driven product and business decisions.

Key Responsibilities:

• Analyse historical and large datasets to understand data sources, identify trends and patterns, and uncover meaningful insights.
• Write complex SQL queries and leverage Python to perform data analysis, ad hoc investigations, and solve business problems.
• Create reports and translate analytical findings into clear, concise, and actionable recommendations for stakeholders.
• Identify opportunities to drive automation and process improvements, improving efficiency and reducing manual effort.
• Communicate data-driven insights effectively to both technical and non-technical stakeholders in a clear and impactful manner.
• Maintain accurate documentation, ensure high-quality deliverables, and consistently meet defined timelines.

Requirements:

• 3–6 years of experience in Data Analytics, Business Intelligence, Data Engineering, or a similar analytical role.
• Strong hands-on expertise in Python and advanced SQL, with the ability to work with and analyse large datasets.
• Experience working with Google Sheets, and implementing automation through data pipelines or workflows.
• Strong analytical and problem-solving skills, with the ability to interpret complex data and derive actionable insights.
• Excellent communication skills with the ability to effectively present methods, results, and recommendations to stakeholders.
• Ability to collaborate effectively with remote and geographically distributed teams across different time zones.

Company Link: https://www.nineleaps.com/

Company LinkedIn: https://www.linkedin.com/company/nineleaps/

Job Description: Senior Java/Python Developer (AI & GenAI Specialist)

Location

Position Summary

We are seeking an experienced Senior Java/Python Developer with strong expertise in enterprise application development and extensive hands-on experience in Artificial Intelligence (AI), Generative AI (GenAI), Large Language Models (LLMs), and AI-powered application development. The ideal candidate will lead the design, development, and deployment of scalable, intelligent solutions that integrate modern AI technologies with enterprise-grade Java and Python ecosystems.

This role requires a combination of strong software engineering skills, AI innovation capabilities, and architectural leadership.

Key Responsibilities

• Application Development

• Design, develop, and maintain scalable enterprise applications using Java and Python.

• Develop RESTful APIs, microservices, and event-driven architectures.

• Build high-performance backend systems using Spring Boot, FastAPI, Flask, or Django.

• Ensure code quality through unit testing, integration testing, and code reviews.

AI & Generative AI Development

• Design and implement AI-powered solutions leveraging Large Language Models (LLMs).

• Develop intelligent applications using OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, and similar platforms.

• Build Retrieval Augmented Generation (RAG) architectures for enterprise knowledge systems.

• Implement AI agents, copilots, chatbots, virtual assistants, and workflow automation solutions.

• Engineer prompts and build prompt orchestration frameworks.

• Develop multi-agent AI systems and autonomous AI workflows.

Required Technical Skills

Core Programming

• Expert-level proficiency in:

o Java (Java 11/17/21)

o Python 3.x

• Strong understanding of OOP, design patterns, and software engineering principles.

Java Technologies

• Spring Boot

• Spring Cloud

• Hibernate/JPA

• Microservices Architecture

• Kafka/RabbitMQ

• REST API Development

Python Technologies

• FastAPI

• Flask

• Django

• Pandas

• NumPy

• Async Programming

Generative AI & LLMs

• OpenAI APIs

• Azure OpenAI

• LangChain

• LangGraph

• LlamaIndex

• Semantic Kernel

• Hugging Face

• Prompt Engineering

• RAG Frameworks

• AI Agent Frameworks

• Vector Databases (Pinecone, Weaviate, ChromaDB, Milvus, FAISS)

Preferred Qualifications

• Experience developing enterprise AI copilots and intelligent assistants.

• Experience implementing AI solutions using Microsoft Copilot Studio, Azure AI Services, or similar platforms.

• Knowledge of AI governance, responsible AI, security, and compliance frameworks.

• Experience in travel, finance, telecom, retail, or large enterprise environments.

• Exposure to graph databases and knowledge graphs.

• Understanding of multimodal AI (text, image, audio, video).

Educational Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or related discipline.

• Generative AI certifications preferred.

Key Competencies

• Solution Architecture

• AI Innovation & Thought Leadership

• Problem Solving

• Stakeholder Management

• Technical Mentoring

• Agile Development

• Analytical Thinking

• Communication & Presentation Skills

Success Metrics

• Delivery of scalable AI-enabled enterprise solutions.

• Reduction in operational effort through AI automation.

• Successful deployment of GenAI applications into production.

• Application performance, reliability, and security.

• Adoption of AI best practices across development teams.

Sr. Technology Architect

Experience Range: 12–15+ years of IT experience, including 3–5+ years in leadership / people management roles.

Location: Chennai, Hyderabad, Bangalore

Qualification: B. Tech /B.E in computer science or equivalent

Minimum 10+ years of experience in Advanced Java

At least 2+ years of experience for the following areas:

• Lead and mentor full-stack development teams across multiple projects and workstreams.
• Define technical architecture, coding standards, and development best practices.
• Drive end-to-end delivery of enterprise applications using Agile methodologies.
• Oversee application design, development, testing, deployment, and production support.
• Ensure adherence to security, performance, quality, and compliance standards.
• Collaborate with clients, product owners, architects, and cross-functional teams.
• Manage resource planning, risk mitigation, technical reviews, and stakeholder communication.
• Promote DevOps, CI/CD, and automation practices to improve delivery efficiency

Must Haves-

• Strong experience in Java Full Stack Development.
• Expertise in Spring Boot and Microservices Architecture.
• Proficiency in Python, Shell Scripting, and backend development.
• Hands-on experience with SQL, Oracle, and PostgreSQL databases.
• Front-end expertise in React, Angular, HTML5, CSS3, Bootstrap, and JSP.
• Experience with Kafka or similar event-driven messaging platforms.
• Strong understanding of API Design, REST Services, and Swagger/OpenAPI.
• Experience implementing security frameworks including OAuth 2.0.
• Hands-on expertise with Jenkins, CI/CD pipelines, and DevOps practices.
• Experience with code quality and security tools such as SonarQube and Fortify.
• Proven people management, stakeholder management, and delivery leadership experience.
• Experience working in Agile/Scrum environments.

Good to Haves-

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of containerization and orchestration technologies such as Docker and Kubernetes/OpenShift.
• Experience with performance tuning, observability, and application monitoring tools.
• Telecom, OSS/BSS, or enterprise digital transformation domain experience.
• SAFe Agile, PMP, Scrum Master, or cloud certifications.
• Exposure to AI-assisted development tools and engineering productivity platforms.

About the company

Metron Security provides automation and integration services to leading Cyber Security companies. Our engineering team works on leading security platforms including - Splunk, IBM’s QRadar, ServiceNow, Crowdstrike, Cybereason, and other SIEM and SOAR platforms. 

Software Engineer is a challenging role within Cyber Security Engineering integration development. The role involves developing a product/service that achieves high-performance data exchange between two or more Cyber Security platforms. A Software Engineer is at the core of the evolution process and is responsible for the End-to-End delivery of the project, right from getting the requirements from customers to deploying the project for them on-prem or on the cloud, depending on the nature of the project. We follow the best practices of engineering and keep evolving. We are agile. 

Each integration needs reskilling yourself with the required technology for that project. If you are passionate about programming and believe in the best practices of software engineering, the following are the skills we are looking for: 

● Developer-centric culture - No bureaucracy or red tape. 

● Chance to work on 200+ security platforms. 

● Opportunity to engage with end-users (customers) and just a cog in the wheel.

About the role

We are looking for passionate developers with 4-7 years of experience in software development to join the Metron Security team as Software Engineers. 

Mandatory Skills 

• 6+ years of experience in software engineering, with a proven track record of leading engineering teams and mentoring junior developers. 
• Expertise in at least one or two Object-Oriented Programming language (Python, typescript, Java,Node.js,Angular, react.js C#, C++) . 
• Good knowledge of Data Structure and its correct usage. 
• Oversee code reviews, ensuring adherence to best practices and maintaining high code quality standards. 
• Imbibe and maintain a strong customer delight attitude while designing and building products/services.

Other Requirements 

• Open to learn any new software development skill if needed for the project.
• Alignment and utilisation of the core enterprise technology stacks and integration capabilities throughout the transition states. 
• Participate in planning, definition, and high-level design of the solution and exploration of solution alternatives. 
• Define, explore, and support the implementation of enablers to evolve solution intent, working directly with Agile teams to implement them. 
• Good knowledge of the implications of Cyber Security on production.
• Experience in architecting & estimating deep technical custom solutions & integrations. 
• Manage the customer to ensure we have a continuous flow of work from them so that the team has enough work for at least a month. 
• Mentor and coach team members, providing technical guidance and fostering professional development. 

Added advantage: 

• Experience in the Cyber Security domain.
• Experience in developing software using web technologies. 
• Experience in handling a project from start to end. 
• Hands-on experience in an Agile Development project and in writing and estimating User Stories. 
• Contribution to open source - Please share your link in the application/resume if any.

Technical Architect – Product Engineering

Experience: 15+ Years

Location: Pune, India

Employment Type: Full-time

About the Role

We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.

The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.

Key Responsibilities

•  Own the overall product architecture and technical roadmap.
•  Design and build scalable, secure, and highly available enterprise applications.
•  Lead the design and implementation of new product features from concept to production.
•  Remain hands-on with coding and contribute to critical product components.
•  Drive architecture reviews, code quality, performance optimization, and engineering best practices.
•  Lead cloud architecture, security, scalability, and DevOps initiatives.
•  Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
•  Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.

Required Skills & Qualifications

•  15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
•  Strong hands-on expertise in Python and modern backend frameworks.
•  Deep experience with AWS services and cloud-native application architecture.
•  Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
•  Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
•  Strong knowledge of SQL and NoSQL databases.
•  Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
•  Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
•  Strong analytical, problem-solving, and decision-making skills.

Job Description:

We are looking for a skilled Python Developer with 2+ years of hands-on experience in backend development and data processing. The ideal candidate should be proficient in Python and have working experience with web frameworks like Flask and FastAPI, along with exposure to data engineering and machine learning workflows.

Key Responsibilities:

Design, develop, and maintain scalable Python applications and APIs using Flask and FastAPI

Work with PySpark and Kafka for real-time data processing

Perform data manipulation and analysis using Pandas and NumPy

Develop and maintain modular, reusable, and testable code following OOP principles

Collaborate with data scientists to integrate ML models (TensorFlow, PyTorch, Scikit-learn) into production

Participate in code reviews, design discussions, and contribute to best practices

Write and maintain documentation for developed modules and workflows

Required Skills:

Strong proficiency in Python programming

Hands-on experience with Flask and/or FastAPI

Experience working with PySpark and Kafka

Solid understanding of Pandas, NumPy, and data handling in Python

Familiarity with TensorFlow, PyTorch, and scikit-learn

Good grasp of Object-Oriented Programming (OOP) concepts

Ability to write modular and maintainable code

Nice to Have:

Understanding of Machine Learning concepts and pipelines

Exposure to Generative AI (GenAI) technologies and tools

Experience with CI/CD tools, Docker, or cloud environments (AWS, GCP, etc.)

Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field

Job Title : SDE 3 – Infrastructure Platform Engineer

Experience : 5.5 to 8.5 Years

Number of Positions : 2

Employment Type : C2H (Contract to Hire)

Work Mode : Remote during contractual period → 5 Days WFO after conversion

Contract Duration : 3 Months

Post-Conversion Location : Pune

Notice Period : Immediate Joiners / Serving Notice Period / Up to 15 Days preferred

(Candidates officially serving a 30-day notice period may also be considered if they are on the bench and have a negotiable joining date)

Role Overview :

We are looking for an experienced SDE 3 – Infrastructure Platform Engineer to design, build, and operate scalable, secure, and highly reliable cloud infrastructure and internal platform capabilities.

The ideal candidate will have strong hands-on experience in Cloud Infrastructure, Infrastructure as Code (IaC), CI/CD, Docker, Kubernetes, automation, observability, networking, and distributed systems.

Mandatory Skills : AWS / Azure / GCP, Terraform / CloudFormation, Kubernetes, Docker, CI/CD, Platform / Infrastructure Engineering, Python / Go / Java / Ruby, Networking, Cloud Security, Distributed Systems, Scalability & Reliability, Strong Coding & Automation.

Key Responsibilities :

• Design and maintain scalable, highly available infrastructure on AWS / GCP / Azure.
• Build and manage Infrastructure as Code (IaC) using Terraform, CloudFormation, or similar tools.
• Develop automation for infrastructure provisioning, deployments, monitoring, and operations.
• Manage and optimize Docker and Kubernetes workloads.
• Build internal platform tools to improve developer productivity and engineering efficiency.
• Implement monitoring, logging, alerting, and observability solutions.
• Participate in incident response, RCA, postmortems, and reliability improvements.
• Design and improve CI/CD pipelines and deployment automation.
• Contribute to system design, architecture discussions, scalability, security, and cost optimization.
• Collaborate with application, data, and product engineering teams.

Required Skills :

• 5.5 to 8.5 years of experience in Infrastructure / Platform Engineering or similar roles.
• Strong hands-on experience with AWS, GCP, or Azure.
• Strong expertise in Terraform / CloudFormation.
• Experience with CI/CD, Docker, and Kubernetes.
• Strong programming skills in at least one of:
• Python, Go, Java, or Ruby.
• Good understanding of networking, cloud security, distributed systems, scalability, and reliability.
• Experience working with production infrastructure and highly available systems.
• Strong troubleshooting and problem-solving skills.

Nice to Have :

• Experience with SRE practices and production on-call ownership.
• Experience in fintech, payments, banking, or transaction-heavy systems.
• Knowledge of cloud security, compliance, or FinOps/cost optimization.
• Experience building internal developer platforms or productivity tools.
• Previous product company experience.

Interview Process :

Round 1 : Take-Home Coding Assignment – Submit within 48 hours

Round 2 : Coding Assignment Discussion – 1 Hour

Round 3 : Technical Managerial Round – 30 Minutes

Note : The take-home coding assignment is mandatory. Candidates should be comfortable completing and submitting the assignment within 48 hours before proceeding.

Ideal Candidate :

Strong Platform / Infrastructure Engineer with hands-on experience in :

Cloud + Terraform / CloudFormation + Kubernetes + CI/CD + Programming + SRE / Production Operations

Pure DevOps profiles without strong coding and platform engineering experience are not preferred.

Experience: 4+ Years 

Location: India (Bangalore, Hyderabad/ Mumbai/ Gurugram)

Role Summary:

AuxoAI is seeking a Senior GenAI Data Engineer with strong fundamentals in data engineering and end-to-end solution design. In this role, you will design and develop production-grade pipelines, leverage GenAI tools (Copilot, Claude, Gemini) to boost development productivity, and define engineering best practices across complex data environments. This is a highly collaborative, cross-functional role — ideal for someone who thrives at the intersection of data engineering excellence and GenAI-powered innovation.

Responsibilities:

• Architect and develop end-to-end data pipelines — from ingestion to transformation to consumption

• Lead solutioning and integration for complex data workflows (batch and streaming)

• Use AI-assisted coding tools (e.g., GitHub Copilot, Claude, Gemini) to accelerate code development, refactoring, and debugging

• Implement robust data quality, testing, lineage, and governance frameworks

• Drive best practices across pipeline performance, reusability, and scalability

• Mentor junior engineers and contribute to capability building within the data team

Requirement:

• 4+ years of experience in data engineering, with expertise in:

      o End-to-end pipeline development (batch and streaming)

      o Data modeling (dimensional, Data Vault, OBT)

      o ETL/ELT design patterns, performance tuning, and optimization

      o SQL (Advanced) and Python (Advanced)

      o Apache Spark for large-scale data processing

• Proficiency using AI coding tools (e.g., Copilot, Claude, Gemini) to enhance productivity and code quality

• Strong understanding of data quality frameworks, unit testing, and CI/CD for data workflows

• Experience with Google Cloud Platform services: o BigQuery, Dataflow, Cloud Composer, Pub/Sub, Dataproc, Vertex AI

• Exposure to finance or sales data domains

• Familiarity with Databricks, Delta Lake, or Apache Iceberg

• GCP Professional Data Engineer certification is a plus

Key Responsibilities

● Lead the architecture, design, development, and delivery of scalable backend services

using Python.

● Own technical direction and architectural decisions for backend systems and services.

● Design and build robust RESTful APIs, microservices, and distributed systems

capable of handling high-scale workloads.

● Design and implement real-time communication systems, including WebSocket-based

services, where required.

● Drive system performance, scalability, reliability, availability, and security.

● Lead performance optimization, capacity planning, monitoring, debugging, and

production issue resolution.

● Establish and promote best practices around code quality, testing, observability, CI/CD,

and production readiness.

● Collaborate closely with frontend, product, DevOps, infrastructure, and other

cross-functional teams to deliver end-to-end solutions.

● Mentor and provide technical guidance to engineers, contributing to overall team growth

and engineering excellence.

● Review code and architecture designs, identify technical risks, and drive improvements

across backend systems.

● Take ownership of complex technical problems and deliver reliable, maintainable,

production-grade solutions.

Required Skills & Qualifications

● 5+ years of software engineering experience, with significant experience in backend

development.

● Strong expertise in Python and experience building production-grade backend

applications.

● Proven experience designing and developing REST APIs and microservices

architectures.

● Strong understanding of distributed systems, scalability, fault tolerance, and

high-availability architectures.

● Hands-on experience with WebSockets and real-time backend integrations.

● Strong experience with SQL/NoSQL databases, caching systems, and data-intensive

applications.

● Experience with performance optimization, monitoring, logging, debugging, and

production operations.

● Strong understanding of software engineering principles, design patterns, and clean

architecture.

● Proven ability to lead technical initiatives and make sound architectural decisions.

● Strong communication, collaboration, and technical leadership skills.

● Experience mentoring engineers and conducting effective code and design reviews.

We are looking for a Python Backend Developer to design, build, and maintain scalable backend services and APIs. The role involves working with modern Python frameworks, databases (SQL and NoSQL), and building well-tested, production-grade systems.

You will collaborate closely with frontend developers, AI/ML engineers, and system architects to deliver reliable and high-performance backend solutions.

Key Responsibilities

• Design, develop, and maintain backend services using Python
• Build and maintain RESTful APIs using FastAPI
• Design efficient data models and queries using MongoDB and SQL databases (PostgreSQL/MySQL)
• Ensure high performance, security, and scalability of backend systems
• Write unit tests, integration tests, and API tests to ensure code reliability
• Debug, troubleshoot, and resolve production issues
• Follow clean code practices, documentation, and version control workflows
• Participate in code reviews and contribute to technical discussions
• Work closely with cross-functional teams to translate requirements into technical solutions

Required Skills & Qualifications

Technical Skills

• Strong proficiency in Python
• Hands-on experience with FastAPI
• Experience with MongoDB (schema design, indexing, aggregation)
• Solid understanding of SQL databases and relational data modelling
• Experience writing and maintaining automated tests
• Unit testing (e.g., pytest)
• API testing
• Understanding of REST API design principles
• Familiarity with Git and collaborative development workflows

Good to Have

• Experience with async programming in Python (async/await)
• Knowledge of ORMs/ODMs (SQLAlchemy, Tortoise, Motor, etc.)
• Basic understanding of authentication & authorisation (JWT, OAuth)
• Exposure to Docker / containerised environments
• Experience working in Agile/Scrum teams

What We Value

• Strong problem-solving and debugging skills
• Attention to detail and commitment to quality
• Ability to write testable, maintainable, and well-documented code
• Ownership mindset and willingness to learn
• Teamwork

What We Offer

• Opportunity to work on real-world, production systems
• Technically challenging problems and ownership of components
• Collaborative engineering culture

Technical Architect – Product Engineering

Experience: 15+ Years

Location: Pune, India

Employment Type: Full-time

Desired Skills: Python, Technical Architecture, AWS, Microservices, SaaS / Multi-tenant Architecture, Kubernetes, System Design

About the Role

We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.

The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.

Key Responsibilities

• Own the overall product architecture and technical roadmap.
• Design and build scalable, secure, and highly available enterprise applications.
• Lead the design and implementation of new product features from concept to production.
• Remain hands-on with coding and contribute to critical product components.
• Drive architecture reviews, code quality, performance optimization, and engineering best practices.
• Lead cloud architecture, security, scalability, and DevOps initiatives.
• Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
• Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.

Required Skills & Qualifications

• 15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
• Strong hands-on expertise in Python and modern backend frameworks.
• Deep experience with AWS services and cloud-native application architecture.
• Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
• Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
• Strong knowledge of SQL and NoSQL databases.
• Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
• Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
• Strong analytical, problem-solving, and decision-making skills.

Job Description-

Experience- 4 to 6 years

Location- Bangalore

As an embedded Full-Stack Developer, you build and operate Python-leaning full-stack features with strong API, CI/CD, and production-support discipline, working alongside an existing squad architecture.

As an embedded Full-Stack Developer, you turn Python + React delivery into reliable, production-grade features.

Key responsibilities

1. Build features. Develop Python-leaning full-stack functionality (React front end secondary).

2. Own APIs. Design and maintain REST APIs integrated with enterprise systems.

3. Automate delivery. Build and maintain CI/CD pipelines; contribute to observability and vulnerability remediation.

4. Support production. Provide production support, triage, and fixes for live services.

5. Collaborate. Work within the existing squad structure and stand-ups.

6. Iterate on quality. Use monitoring and feedback to improve reliability and performance.

Must-have qualifications

• Python-leaning full-stack development (React preferred secondary); 3-15 years depending on level

• Strong API design and integration experience

• CI/CD pipeline experience

• Production-support experience (triage, incident response, fixes)

AI Agent Frameworks, LangChain, LlamaIndex, OpenAI API,Zapier, HTML5, CSS3, JavaScript,bootstrap3.1,TypeScript, React.js, Next.js, Vue.js, Node.js, Python, PHP, WordPress, Headless CMS, DNS Management, SSL Configuration, Conversion Rate Optimization (CRO), A/B Testing, AWS, Google Cloud Platform (GCP), Cloudflare CDN, AWS S3, Core Web Vitals, Google Trends, Google Search Console, Ahrefs, SEMrush, Google Analytics 4 (GA4), Google Tag Manager (GTM), Meta WhatsApp Cloud API, Twilio, Webhooks, MSG91, REST APIs,claude,github,MYSQL

Junior Game Developer

Location: Bangalore

Experience: 6 Months – 1.5 Years

Joining: Immediate Joiners Preferred

Employment Type: Full-Time

About the Role

We are looking for a Junior Game Developer with hands-on experience in game development and a strong interest in building interactive 2D/3D exergames. The candidate should be comfortable working across game logic, gameplay systems, UI, assets, scenes, and performance optimization.

Key Responsibilities & Skills

• Proficiency in at least one programming language: C++, C#, Python, or JavaScript.
• Hands-on experience with Godot, Unity and development of 2D and 3D games.
• Ability to develop game features end-to-end, including game logic, gameplay mechanics, UI, characters, assets, and scene building.
• Basic understanding of real-time rendering, GPU/CPU performance, memory management, profiling, and optimization.
• Experience with Blender and game asset creation/integration.
• Familiarity with AI-assisted asset generation and AI/LLM tools for coding, debugging, development, and optimization.
• Good understanding of OS concepts, processes, threads, memory management, and computer architecture.
• Experience with Git/version control and familiarity with CI/CD is an advantage.

Good to Have

• Experience with Three.js or Phaser.
• Exposure to MediaPipe, TensorFlow Lite, or ONNX Runtime.
• Understanding of hardware-accelerated AI/ML inference.
• Experience developing for low-compute/resource-constrained devices.
• Interest or experience in exergames, fitness technology, AR/VR, or interactive applications.

Candidate Profile

• 6 months – 1.5 years of relevant game development experience.
• Strong problem-solving and debugging skills.
• Willingness to learn and work with emerging technologies.
• Ability to work independently as well as collaboratively.
• Immediate joiners will be preferred.
• Candidates should have a portfolio/GitHub or playable game projects demonstrating their skills.

Golang Developer

Experience: 6-8 years

Employment Type: Contractual, Full-time

Desired Skill: Golang, GRPC, RestAPIs, AWS

Work Mode: Pune, India

Availability: Immediate Joiners

This is the contractual opportunity on a full time basis.

Must have skills:

● 6+years of Software Development experience

● 5+years of GoLang programming; Prefers additional proficiency in either Java or Python

● Knowledgeable in writing REST APIs

● Comfortable programming in production grade systems

● Experience with building HTTP based services

● Strong background of optimizing performance

● Familiarity with event-driven systems

● Experience dealing with highly concurrent, distributed architectures/systems.

Good to have skills:

• Exposure to relational databases
• Experience with Cloud Providers such as AWS is an advantage; cloud privileged access (CIEM, IAM roles, ephemeral credentials)
• Experience using Terraform to manage infrastructure as code would be an advantage
• Hands-on experience building or extending Privileged Access Management (PAM) capabilities — credential vaulting, secrets management, password rotation, just-in-time / time-bound privileged access
• Working knowledge of privileged session management and session recording — session proxying/brokering, keystroke and video capture, session replay, live monitoring and termination, tamper-evident audit trails
• Familiarity with remote access protocols and gateways — SSH, RDP, HTTPS/web-based sessions; protocol proxying and man-in-the-middle session interception

Job Description:

• Infrastructure Management: Design, implement, and manage scalable, reliable, and secure cloud infrastructure using AWS, GCP, and/or Azure.
• CI/CD Pipelines: Develop and maintain continuous integration and continuous deployment (CI/CD) pipelines to streamline the development lifecycle.
• Automation: Automate infrastructure provisioning, configuration management, and application deployment processes.
• Monitoring and Performance: Implement monitoring, logging, and alerting solutions to ensure system health, performance, and reliability.
• Security: Ensure the security of cloud infrastructure and applications, including identity management and compliance with industry standards.
• Collaboration: Work closely with client and development teams to integrate DevOps practices and deliver high-quality software.
• Documentation: Maintain comprehensive documentation of infrastructure, configurations, and processes.
• Innovation: Stay current with emerging technologies and industry trends, integrating them into the DevOps strategy as appropriate.

Qualifications: 

• Education: Bachelor's degree in Computer Science, Information Technology, or a related field.
• Experience: 7-9 years of overall experience with relevant experience of at least 5 years in DevOps and served as a lead or senior engineer.

Job Description

• Lead Custom Odoo Application Design and Development: Provide leadership in designing and developing custom Odoo applications, ensuring alignment with business requirements and scalability.
• Collaborate Across Teams: Foster effective collaboration with cross-functional teams, including business analysts, project managers, and quality assurance, to identify and implement innovative solutions.
• Manage Odoo Application Lifecycle: Oversee the complete lifecycle of Odoo applications, from initial design and development to ongoing maintenance and upgrades for optimal performance.
• Technical Issue Resolution: Take a proactive role in troubleshooting and efficiently resolving technical issues during development and maintenance phases to ensure a seamless user experience.
• Mentor and Develop Team: Lead and mentor a team of developers, fostering their growth and development within the Odoo development domain.
• Stay Current with Odoo Framework Advances: Stay abreast of the latest developments in the Odoo framework and related technologies, incorporating new knowledge into ongoing projects.
• Drive Innovation and Best Practices: Champion innovation and best practices in Odoo development, driving the adoption of efficient and effective methodologies within the team.
• Client Interaction: Engage with clients to understand their business requirements, provide technical insights, and ensure the successful delivery of Odoo solutions.

Desired Skills:

• Bachelor’s degree in a related field or Computer Science.
• Minimum of 7 years of experience in software development, with a substantial focus on Odoo development.
• Strong proficiency in Python, XML, and SQL, showcasing advanced technical skills in designing and developing robust Odoo solutions.
• Proven leadership skills, with the ability to lead and mentor a team of developers effectively.
• Excellent problem-solving skills, demonstrating an ability to address complex challenges independently or collaboratively.
• 3wedStrong communication skills to facilitate effective interactions with team members, clients, and other stakeholders.
• Experience working with Agile methodologies and advanced proficiency in Git version control.

About the Role

Shava Studios is building AI-native software products. We are hiring a Mid Senior Full-Stack Engineer to own features end-to-end across the frontend and backend, with depth in system architecture and the AI and real-time systems that connect them. We hire for demonstrated ability rather than years of experience.

Technical Environment

1. Frontend: Next.js (App Router), React, TypeScript, Tailwind CSS, MUI, Radix UI, TanStack Query, Zustand, NextAuth; Remotion for in-browser video editing and rendering.
2. Backend: Python, FastAPI, SQLAlchemy with PostgreSQL and Alembic, Pydantic; hexagonal (ports-and-adapters) microservices.
3. Async & Real-Time: Celery with RabbitMQ, Redis and Redis Streams, server-sent events, and WebSockets.
4. AI: LangGraph, deepagents, and LangChain for agent orchestration across multiple GenAI providers (OpenAI, Google, and others).
5. Tooling & Quality: Vitest, Playwright, Testing Library, pytest, Hypothesis; ruff and mypy; TDD with a strict line-and-branch coverage gate; Docker; CI on Azure Pipelines.

Responsibilities

1. Design, build, and ship full-stack features end-to-end across the UI, backend services, and async job pipelines.
2. Design and evolve service APIs, data models, and database schemas with migrations.
3. Architect and integrate LLM/agent and other AI capabilities behind clean, provider-agnostic abstractions.
4. Build and harden real-time systems (WebSockets, server-sent events, streaming) with reliable delivery and reconnection semantics.
5. Design asynchronous processing pipelines: queuing, workers, retries, idempotency, and failure recovery.
6. Manage third-party integrations (payments, AI providers, storage) behind well-defined interfaces.
7. Optimize frontend and backend performance, state management, and scalability.
8. Own security-sensitive concerns: authentication, authorization, secret handling, and secure service-to-service communication.
9. Instrument observability: logging, metrics, tracing, and structured error handling.
10. Uphold and evolve the architecture and engineering standards through technical design and code review.
11. Mentor engineers and raise the quality bar across the team.

Requirements

1. Proven full-stack delivery across a React/TypeScript frontend and a Python (or comparable) backend.
2. Sound judgment on architecture, API design, and data modeling, with the ability to articulate trade-offs.
3. Rigorous testing discipline and comfort with TDD and high coverage standards.
4. Ability to work with LLM/GenAI systems; direct experience preferred, though strong engineers eager to learn are welcome.
5. Technical leadership: thoughtful code review, clear technical writing, and a focus on root-cause fixes.

Nice to Have

1. Production experience with LLM/agent systems (LangGraph, LangChain, or similar).
2. Media or video pipelines: encoding, timeline editors, or serverless rendering.
3. Async worker systems (Celery, RabbitMQ, Redis).
4. Payments/billing and metering systems under concurrency.
5. Hexagonal architecture, ports-and-adapters, or DDD experience.

Growth

The role offers substantial influence over architecture and a clear path toward staff-level technical leadership for engineers who raise the team's standards.

• We are looking for experienced AI/ML Architects to join our AI Engineering service line. In this role, you will anchor the technical delivery of enterprise AI/Agentic AI projects post deal-closure. You will take over from solution architects and lead the design, build, deployment, and optimization of AI/ML systems — ensuring production-grade quality, scalability, and compliance. 
• You will interface with cross-functional teams, manage engineering complexity, and ensure value realization for customers across industries such as BFSI, HLS, Manufacturing, CMT, Retail, and Energy. 

Key Responsibilities

Architecture & Technical Leadership

Hands-on Engineering & Problem Solving

Required Qualifications

Education : B.Tech/M.Tech or equivalent in Computer Science, Data Science, or a related field.

Experience

● 10+ years in software architecture or engineering with 5+ years in applied AI/ML

system delivery.

● Experience in productionizing AI/ML models and building full-stack AI applications in

enterprise settings.

● Strong Python development skills; proficiency in ML/AI frameworks (PyTorch,

TensorFlow, Scikit-learn).

● Strong understanding of LLMs, RAG pipelines, vector databases (Weaviate, Qdrant,

Pinecone).

● Experience with MLOps/LLMOps tools: MLflow, Argo, KServe, Feast, Kubeflow.

● Proficiency in data pipeline engineering using Spark, Airflow, or DataFlow.

● Exposure to agent orchestration frameworks: LangChain, LangGraph, AutoGen,

CrewAI is a big plus.

● Cloud & Infrastructure

● Hands-on experience with GCP (Vertex AI, BigQuery, Document AI, AI Gateway)

and/or Azure (Azure ML, OpenAI, Synapse).

● Expertise in containerization (Docker) and orchestration (Kubernetes).

● Familiarity with Infrastructure as Code (Terraform, Pulumi, CDK).

Soft Skills

Strong architectural thinking and problem-solving in fast-paced delivery environments.

Excellent communication and collaboration skills to work across cross-functional teams and

clients.

Proactive, structured, and detail-oriented with a bias for execution.

Nice to Have

Experience in real-world deployments of Agentic AI systems or collaborative multi-agent setups.

Exposure to regulatory/ethical concerns in AI such as fairness, transparency, or bias mitigation.

Familiarity with AI observability, explainability, and governance tooling (e.g., Arize, Fiddler,

TruEra).

Nature of Assignment

• We are looking for an experienced Senior Software Engineer – Backend Development to develop and enhance enterprise-grade scientific and workflow-driven software solutions. The role requires strong technical expertise in Python-based backend 

development, API design, microservices, and modern software engineering practices.

• As a senior member of the engineering team, you will own the design, development, testing, and delivery of complex software components while collaborating closely with Product Management, Quality Engineering, Front-End Development, DevOps, and global engineering teams. The ideal candidate is passionate about building high-quality software, solving complex technical problems, and delivering reliable, maintainable, and scalable solutions.

Key Responsibilities

• Design, develop, and maintain scalable, secure, and high-performance backend applications using Python, FastAPI, and Uvicorn.

• Design and implement RESTful APIs, Backend-for-Frontend (BFF) services, and microservices that support complex business workflows and enterprise integrations.

• Drive modernization initiatives by refactoring legacy applications into modular, cloudready, service-oriented architectures.

• Implement robust business logic, validation, exception handling, asynchronous processing, data persistence, reporting, and workflow orchestration following industry best practices.

• Ensure secure coding practices by applying web application security principles, authentication and authorization standards, and vulnerability mitigation techniques.

• Own end-to-end delivery of features from requirement analysis and technical design through development, testing, deployment, and production support.

• Analyze, troubleshoot, and resolve complex product, integration, and production issues using logs, debugging tools, and root-cause analysis techniques.

• Develop comprehensive unit, integration, API, and regression tests to ensure software quality and reliability.

• Support CI/CD processes, deployment validation, release readiness, and environment verification activities.

• Contribute to technical documentation, API specifications, and knowledge-sharing initiatives.

• Collaborate closely with Product Management, UI teams, QA, DevOps, and Architecture teams to deliver high-quality software solutions.

• Mentor junior engineersthrough code reviews, technical guidance, and knowledge sharing.

Qualification/s

• Bachelor’s/master’s degree in computer science, Software Engineering, Information Technology, or a related discipline.

Technical Expertise

• Strong hands-on software development experience in Python backend development.

• Extensive experience developing REST APIs using FastAPI, Uvicorn, and modern Python ecosystem frameworks.

• Strong understanding of microservices, distributed systems, API-first design, and Backend-for-Frontend (BFF) architecture.

• Proficiency in Object-Oriented Programming (OOP), SOLID principles, design patterns, and clean code practices.

• Solid experience in asynchronous programming, dependency injection, API validation, exception handling, and performance optimization.

• Strong knowledge of web application security including OAuth2, JWT, OpenID Connect, SSO, secure coding practices, OWASP principles, and vulnerability remediation.

• Strong knowledge in Logging, Monitoring & Troubleshooting – Production support, observability, performance tuning, and root-cause analysis.

• Hands-on experience with Git, branch management strategies, pull requests, and collaborative development workflows.

• Experience building and maintaining CI/CD pipelines using modern DevOps tools and automated release processes.

• Hands-on experience in testing frameworks such as PyTest and automation of units, integration, API, and regression testing.

• Experience with SQL /NoSQL databases, data modeling, query optimization, and backend data management.

• Strong debugging, analytical, and problem-solving skills with the ability to diagnose issues across applications, infrastructure, and deployment layers.

• Experience independently leading technical initiatives and delivering production grade software solutions

• Excellent collaboration and communication skills within cross-functional Agile teams

Position Summary

We are looking for a strong hands-on Software Engineer to develop and maintain Python 3.10 backend services and FastAPI-based Backend for Frontend (BFF) for the CryoFlow platform. You will address the assigned tasks, understand the expected behavior, implement 

clean and well-tested code, and validate your work end to end.

This role suits an engineer who codes well, thinks through problems methodically, learns quickly in an unfamiliar domain, and takes pride in delivering features that work reliably in real product conditions. You will work closely with senior engineers, QA and front-end developers, and will participate in client feedback meetings to understand how your work is used.

Key Responsibilities

• Contribute to the refactor of existing backend capabilities into Python 3.10 services aligned with CryoFlow architecture and deployment practices.

• Develop and maintain REST APIs, Microservices, BFF using FastAPI and Uvicorn, exposing clear APIs for product workflows, integration screens and front-end consumers. 

• Follow team coding standards, branching strategy, review process and API conventions consistently

• Implement backend logic for status updates, validation, data persistence, device/session edge cases, report-generation helpers and user-facing error handling.

• Deliver assigned backlog items and tasks on schedule, with clean, readable and maintainable code.

• Participate in design discussions and reviews; propose simple, practical approaches and incorporate feedback well.

• Write and maintain tests for Python services and integration flows, including API tests, BFF route tests and mocked external calls.

• Debug across backend code, API responses, logs, databases and front-end symptoms with support from senior engineers where needed.

• Work closely with front-end developers on Angular integration and help debug integration issues.

• Collaborate with QA on test scenarios, defect reproduction and verification.

• Participate in client feedback and review meetings; understand feedback, capture action items and follow through.

Qualifications

• Bachelor’s or Master's degree in computer science, Software Engineering, Information Technology, or a related discipline.

Essential Skills 

Technical Expertise

• 5+ years of hands-on software development experience in backend or API-oriented applications.

• Strong Python programming skills, ideally with Python 3.10, in backend services or APIoriented applications.

• Hands-on experience with FastAPI and Uvicorn, including route design, validation, dependency injection patterns, async behaviour and logging.

• Working experience with or exposure to BFF layers that adapt backend/domain services for front-end workflows.

• Good understanding of REST APIs, data validation, error handling and service-toservice calls.

• Awareness of Microservice architecture and the trade-offs involved in service design.

• Strong problem-solving and debugging skills across code, APIs, logs and databases.

• A practical testing mindset: unit tests, API tests, mocks/fixtures and regression checks.

• Very good written and verbal communication skills.

• Ability to work independently on assigned tasks and collaborate effectively within a team.

Preferred Skills

• Familiarity in developing software for scientific instruments, laboratory automation, imaging systems, life sciences, healthcare technologies, medical devices, industrial automation, or other hardware-integrated software platforms.

• Familiarity to Angular v.17 front-end frameworks for integration and debugging.

• Familiarity with Docker, Kubernetes, container orchestration, observability, and production monitoring.

• Experience working in regulated or quality-controlled software development environments

Sr.Data Scientist,Python, AI ML

We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.

We are a San Francisco-based AI infrastructure company working with leading frontier AI labs to build post-training data and evaluation infrastructure for foundation models. We are hiring a Python Developer to create high-quality datasets, reinforcement learning environments, and benchmarking pipelines used to improve and evaluate state-of-the-art LLMs. This is a remote role with flexible working hours.

Responsibilities

* Create and curate datasets for LLM post-training (SFT, RLHF, RL, preference optimization).

* Build and maintain RL environments for agent evaluation.

* Develop Python tooling for dataset generation, validation, and transformation.

* Evaluate models on custom benchmarks and testing pipelines.

* Collaborate with research and engineering teams to deliver client-specific post-training datasets.

* Work with terminal-first development workflows and cloud infrastructure.

Required Skills

* Strong Python programming skills.

* Understanding of LLM fundamentals and post-training concepts (SFT, RLHF, RL).

* Experience working with structured data (JSON, CSV, YAML).

* Git, Linux/Unix command line, and solid software engineering fundamentals.

Good to Have

Experience with RAG, agentic AI systems, Hugging Face Transformers, LoRA/PEFT, LangChain or LlamaIndex, vector databases (FAISS, Qdrant, Milvus, Pinecone, Weaviate, ChromaDB), Docker, AWS/GCP, FastAPI/Flask, Bash, CLI tooling, model evaluation frameworks, benchmarking, and AI infrastructure.

Compensation

Base Salary: USD $1,250/month

Equity: ESOP/Equity package included.

Performance Bonuses: Up to USD $4,000/month (in addition to base salary).

Location

Remote (Worldwide)

Work Hours

Flexible, remote-first, asynchronous work environment.

How to Apply

Apply here: https://tally.so/r/wLReJG

Please complete the application form and submit the required details. Only shortlisted candidates will be contacted.

Data Engineer

Location: Bengaluru, India (Hybrid)

Employment Type: Full-time

Experience: 3-5 years

Role Overview  

What We’re Looking For:

• Bachelor’s degree in Computer Science/Engineering or equivalent experience required.
• Experience designing and shipping cloud services products.
• Experience driving and managing technical and architectural dependencies on AWS Cloud.
• A firm understanding of system architecture, cloud computing, PaaS/SaaS design principles, S3, DynamoDB, RDS mandatory.
• Experience in building or maintaining ETL processes and tools, i.e., AWS Glue or any open-source tool.
• Proven system-level design contribution to a current “Live” (in production / under daily high load) multi-region SaaS or PaaS offering.
• Proven experience with S3, DynamoDB, SQL, and AWS RDS services.
• Proficiency in programming languages such as Python.
• Strong analytical and problem-solving skills.
• 
  

Required Skills & Experience

• Experience with Python, SQL, and data visualization/exploration tools.
• Familiarity with the AWS ecosystem, specifically S3, DynamoDB, and RDS.
• Communication skills, especially for explaining technical concepts to nontechnical business leaders.
• Ability to work on a dynamic, research-oriented team that has concurrent projects.
• Experience in AWS cost optimization (Savings Plans, Reserved Instances, Spot Instances) and governance frameworks.
• Experience developing solutions using infrastructure orchestration tools (SSM, automation account, Ansible, etc.).
• Excellent leadership, stakeholder management, and communication skills.

What We Offer

• Work with some of the brightest minds in the emerging EV industry.
• Make a tangible impact in reducing carbon emissions and enabling sustainable energy.
• Freedom to suggest, implement, and innovate on systems, processes, and technologies.
• Daily ownership in a high-growth, challenging environment.
• Flexible work environment with hybrid schedules and virtualization options.
• Competitive pay and benefits including health coverage, innovative PTO program, and performance bonuses.

We are seeking a Senior Full Stack Engineer to join our team in a long-term contractor capacity to continue development of a production-grade platform hosted on AWS.

This application supports policy processing, third-party integrations, compliance workflows, reporting, and intelligent automation capabilities. The ideal candidate is a strong software engineer first, capable of contributing across the full stack while helping scale and evolve the platform.

This role requires someone who can step into an existing system, understand complex workflows quickly, and independently deliver high-quality solutions.

Responsibilities

• Design, develop, and maintain full-stack application features across frontend and backend systems

• Build and support integrations with third-party systems and APIs

• Develop workflow-driven processes using Temporal

• Build scalable APIs and backend services using Python

• Maintain and optimize relational databases using PostgreSQL

• Develop reporting and analytics capabilities using charting libraries

• Contribute to AI-enabled features and integrations within the platform

• Improve CI/CD pipelines and deployment processes

• Participate in architecture discussions and help shape long-term technical direction

• Work closely with business and technical stakeholders to deliver production-ready solutions

Required Qualifications

Engineering

• at least 7+ years of full stack software engineering experience

• Strong proficiency in Python

• Strong frontend development experience with modern web frameworks

• Strong backend API development experience

• Experience designing and building scalable applications

• Strong understanding of software architecture and best practices

• Experience working in complex, integrated systems

Workflow and Orchestration

• Proven experience with Temporal

• Experience building and managing workflow orchestration patterns

• Familiarity with asynchronous processing and event-driven systems

Database and Reporting

• Strong experience with PostgreSQL

• Strong SQL and data modeling experience

• Experience building reporting dashboards and analytics features

• Experience with charting libraries such as Chart.js, D3.js, or Plotly

DevOps

• Experience with CI/CD pipelines

• Familiarity with containerized deployments

• Experience with cloud environments and modern development workflows

Preferred Qualifications

• Experience in insurance, surplus lines, or compliance-based applications

• Experience integrating with third-party vendors and external APIs

• Experience with AI tooling, LLM integrations, and context engineering

• Experience building intelligent automation features

What We Are Looking For

• Self-driven and highly autonomous

• Strong problem-solving ability

• Comfortable with ownership and accountability

• Able to contribute with minimal supervision

• Strong communication skills in English

• Comfortable working U.S.-based business hours

Ideal Candidate

A senior full stack engineer who can quickly contribute to an active production system, own features end-to-end, and help expand a platform that sits at the center of complex business workflows and integrations. Send resume with projects and contact information.

Senior Software Engineer – Backend

Company: House of EdTech (Goenka Kachave LLP)

Location: Bangalore, Hybrid

Job Type: Full-Time

Experience: 5+ Years

About the Role

House of EdTech is looking for a Senior Software Engineer – Backend to design, develop, and scale high-performance backend services and APIs supporting products used by millions of learners.

You’ll work closely with Product, Frontend, Data, and Engineering teams while taking end-to-end ownership of backend features and contributing to system architecture and technical decisions.

What You'll Do

• Design and develop scalable backend services and REST APIs.
• Build reliable systems capable of handling high traffic and large data volumes.
• Own backend features from design and development through deployment and monitoring.
• Work with microservices, databases, and distributed systems.
• Identify and solve performance, scalability, reliability, and security challenges.
• Participate in system design and architecture discussions.
• Conduct code reviews and contribute to engineering best practices.
• Mentor junior and mid-level engineers.
• Monitor production systems and troubleshoot incidents.

What We're Looking For

• 5+ years of professional backend development experience.
• Strong hands-on experience with Java, Python, Scala, C++, or a similar language.
• Experience building and operating large-scale distributed systems.
• Strong understanding of REST APIs, microservices, and databases.
• Experience with cloud/infrastructure technologies such as GCP, Docker, or Kubernetes.
• Strong software engineering fundamentals, including security, reliability, testing, and code quality.
• Experience with system design, architecture, and technical decision-making.
• Strong communication and cross-functional collaboration skills.
• Experience mentoring engineers is a plus.

Why Join House of EdTech?

• Work on products impacting millions of learners.
• Solve challenging backend and scalability problems.
• Take significant ownership of architecture and engineering decisions.
• Opportunity to grow into technical leadership and architectural ownership.
• Work in a fast-growing technology environment.

We are seeking an experienced Solution Architect with deep expertise in Firewalls and Load Balancing, to lead the design, implementation, and optimization of our network strategy. The ideal candidate will possess a strong technical background, hands-on experience with Fortinet Firewalls (mandatory), F5 LTM (mandatory), Infra as code python/ansible (mandatory), Palo Alto Firewall (nice to have) and Cloudflare (nice to have), and a proven track record of delivering secure, scalable, and robust solutions in complex environments. 

Solution Architecture and Design :

• Architect for design, implementation and upgrade of firewalls solutions, • Analyze current business processes, IT infrastructure, and security requirements to develop security for our network solution.

• Develop high-level and detailed architecture diagrams, technical documentation, and integration designs.

• Ensure solutions align with enterprise security architecture, regulatory requirements (GDPR, SOX, etc.), and industry best practices.

Technical Competencies

Bachelor’s or master’s degree in computer science, Information Security, or related field.

• Strong expertise on Fortinet Firewalls - including rules management, FortiGate Managers, IPSec tunnels, firewall upgrade

• Strong expertise in F5 Load balancers, LTM module (APM nice to have)

• Strong Expertise on Infra As code python/Ansible, proven deployments of API based scripts to manage or reports Firewall or Load Balancers

• 10+ years of experience in complex network environments with 100+ firewalls

• Proven experience with Managing rules and managing upgrades on Fortigate environment (with FortiManager and FortiAnalyzer)

• Certification: Fortinet certification mandatory, F5 certification appreciated

• General shift business hours: from 10:30 AM to 7:30 PM IST

AI & Data Engineering – Role Overview

What You’ll Do

🤖 AI Architecture & Agentic Deployment

• Design, develop, and deploy production-grade AI applications and intelligent agents using Azure AI Foundry.
• Build scalable, secure, and fully governed enterprise AI solutions.

📊 Data Foundations & Modernization

• Architect high-performance data models and automated pipelines using Azure Databricks, Python, and Apache Spark.
• Modernize legacy systems and tune Spark clusters for performance.

🧠 LLMs & Prompt Engineering

• Apply advanced prompt engineering techniques.
• Fine-tune LLM workflows and manage enterprise AI integrations across complex business environments.

👨‍💻 Technical Leadership & Mentoring

• Act as the primary Subject Matter Expert (SME) for AI and data engineering.
• Design end-to-end architectures and mentor junior engineers.
• Actively contribute to technical guilds and communities of practice.

🤝 Strategic Stakeholder Management

• Translate data and AI strategy into robust IT solutions.
• Present findings, metrics, and architectures to technical teams and business leaders.
• Drive technology adoption and alignment across stakeholders.

⚙️ Operations & Change Governance

• Oversee incident, problem, and change management processes for production AI and data workflows.
• Ensure high availability, speed of delivery, and cost efficiency.

What We’re Looking For

• 6+ years of high-impact engineering experience architecting, building, and deploying LLM applications, custom agents, and governed AI solutions on Azure AI Foundry.
• Deep proficiency in Python for data pipeline engineering and custom AI development.
• Advanced technical expertise in Azure Databricks, including:
• PySpark
• Cluster optimization
• Modern lakehouse design
• Strong foundation in:
• SQL
• High-volume ETL/ELT pipeline design
• Data modeling frameworks
• Deep knowledge of:
• Prompt engineering
• LLM orchestration
• Evaluation frameworks
• AI guardrails within Azure ecosystems
• Outstanding communication skills, with a proven ability to influence both technical teams and non-technical business stakeholders.

What You’ll Get

Your work matters—and so do you. That’s why we back your skills with a structure that supports your development, celebrates your wins, and helps you keep growing professionally and personally.

🚀 Growth & Development

• Accelerate Your Career: Lead delivery across diverse industries and cutting-edge technologies while expanding your leadership mindset.
• Access Global Brands: Engage directly with world-leading businesses and manage relationships at the executive level.
• Proprietary Frameworks & Accelerators: Use established playbooks and toolkits to fast-track meaningful work and project outcomes.
• Paid Certifications: Stay ahead with certifications across ITIL, PMP, and major cloud platforms.

🏆 Culture & Rewards

• Supportive Leadership: Benefit from senior mentoring and clear pathways into practice leadership or account management.
• 360° Progress Reviews: Receive honest, developmental feedback to fuel your professional growth.
• Guilds & Weekly Training: Learn from peers through communities focused on data, AI, and delivery excellence.
• Hackathons & Innovation Days: Challenge yourself to build innovative solutions beyond business as usual.
• Kudos & Recognition: Great work doesn’t go unnoticed, supported by impact-based rewards and incentives.
• Vivanti Articulate: Master executive communication through a specialized public-speaking program.
• Employee Assistance Program: Access support for medical, mental, and personal wellbeing.
• Real Connection: Enjoy Friday socials, team-building days, and a collaborative team environment.

Final Word

If you're looking for a place where your growth goes into overdrive, where you'll work with great people, gain access to cutting-edge technology, and genuinely enjoy the journey—this could be the opportunity for you.

Role overview

The client is building a multimodal AI platform that processes multi-hour video, audio and text to generate structured insights, narratives and highlight workflows for broadcasters and media organisations.

We are seeking a Backend / Platform Engineer to design and build high-throughput media pipelines, robust APIs, and model-serving infrastructure that connect our AI engine (video perception + multimodal reasoning) to real products and customer environments.

This is not a CRUD‑only backend role.

You will work on:

• long‑running jobs
• distributed processing
• GPU inference orchestration
• storage for embeddings and metadata
• integration with AI models
• reliability and observability at scale

Key responsibilities

Media ingestion & processing pipelines

• Design and implement ingestion pipelines for multi‑hour video and audio content.
• Build microservices for frame extraction, audio processing, transcription integration and metadata generation.
• Handle long‑running, asynchronous jobs using queues, workers and robust retry strategies.
• Integrate with FFmpeg or similar tools for transcoding, segmenting and preparing media for AI models.

API & platform architecture

• Design and implement REST/gRPC APIs that expose AI model outputs (perception, multimodal alignment, narratives) to frontend and external systems.
• Define clear contracts for internal services and external integrations.
• Implement authentication, authorisation and rate‑limiting for platform endpoints.
• Ensure backward‑compatible API evolution as the product matures.

Model‑serving & AI integration

• Integrate with AI inference services (video models, multimodal models, LLM/VLM) running on GPUs or specialised infrastructure.
• Design request/response flows that handle large payloads, streaming outputs and structured results.
• Optimise throughput and latency for inference pipelines, including batching, caching and concurrency control.
• Collaborate closely with AI engineers to productionise models and debug end‑to‑end behaviour.

Storage, data models & performance

• Design data models to store embeddings, timelines, metadata, scene/shot boundaries, and narrative units.
• Work with appropriate storage technologies (SQL/NoSQL, object storage, search indices) based on access patterns.
• Implement indexing and query strategies for fast retrieval of segments, highlights and multimodal insights.
• Optimise performance for large datasets and high‑volume workloads.

Reliability, observability & operations

• Implement logging, metrics and tracing across services for debugging and monitoring.
• Set up health checks, circuit breakers and graceful degradation for critical services.
• Work with CI/CD pipelines to ensure safe, repeatable deployments.
• Collaborate on Kubernetes‑based deployments (or equivalent orchestration) for scaling services.

Requirements (must‑have)

Experience:

• 4–8 years in backend or platform engineering.
• At least 3 years working on distributed systems, high‑throughput services or complex pipelines (not just simple CRUD apps).

Languages & frameworks:

• Strong proficiency in Python or Node.js (one primary, both are a plus).
• Experience with at least one modern backend framework (FastAPI, Flask, Express, NestJS, etc.).

Distributed systems & pipelines:

• Hands‑on experience with queues and workers (e.g. Celery, RabbitMQ, Kafka, SQS, etc.).
• Experience building asynchronous, long‑running job pipelines.
• Understanding of idempotency, retries, backoff, and failure handling.

APIs & integration:

• Strong experience designing and implementing REST APIs (gRPC is a plus).
• Experience integrating with external services and handling network‑level failures.

Cloud & infrastructure:

• Experience deploying services on AWS, GCP or Azure (EC2/Compute Engine, S3/GCS, IAM, networking basics).
• Experience with Docker; exposure to Kubernetes is a strong plus.

Data & storage:

• Experience with SQL and at least one NoSQL store.
• Ability to design schemas and data models for performance and maintainability.

Engineering quality:

• Strong debugging skills across services and environments.
• Experience with unit/integration tests for backend systems.
• Clear, structured communication in English.

Nice‑to‑have

• Experience with media/video processing (FFmpeg, transcoding, segmenting).
• Experience with AI/ML model integration (serving models, handling inference requests).
• Experience with search/retrieval systems (e.g. Elasticsearch, vector databases).
• Experience with observability stacks (Prometheus, Grafana, OpenTelemetry).
• Experience working with remote teams across time zones.

What we are explicitly NOT looking for

To reduce noise and mismatches, we are not looking for:

• Pure CRUD‑only backend developers with no pipeline or distributed systems experience.
• Engineers who have only worked on small, single‑service apps without scale or complexity.
• Candidates who cannot explain trade‑offs in architecture, data modelling and reliability.
• Candidates who are uncomfortable with ownership of subsystems end‑to‑end.

Why join us

• Work on real, complex problems at the intersection of media, AI and distributed systems.
• Collaborate with senior AI engineers working on perception, multimodal fusion and narrative reasoning.
• Build the core platform that turns AI models into a usable product for broadcasters and media organisations.
• Operate with high ownership, clear expectations and direct access to the CTO.

Role Descriptions: Azure data engineer

SN Required Information Details

1 Role** Azure Cosmos DB Developer

2 Required Technical Skill Set** Primary - PySpark Azure Cosmos DB

Secondary -Python, Microsoft Fabric

3 No of Requirements** 4

4 Desired Experience Range** 8 to 12

5 Location of Requirement Pune

Desired Competencies (Technical/Behavioral Competency)

Must-Have**

1. Deep hands-on experience with Python,Pyspark,Spark batch,notebook in Azure

2. Experience in Cosmos DB – including data modeling, indexing, partitioning, consistency levels, and performance tuning.

3. Strong understanding of Cosmos DB APIs (Core SQL API, MongoDB API, etc.) and integration patterns.

4. Proficiency in query optimization and troubleshooting Cosmos DB performance issues.

5. Experience in data processing using PySpark and Python.

6. Familiarity with Microsoft Fabric for data engineering and analytics workflows.

7. Proficient using source code management tools such as Git or GitHub

8. Experience with Test Driven Development and / or Behavior Driven Development.

Good-to-Have 1. Exposure to data governance tools like Azure Purview.

2. Familiar with various design patterns

3. Familiar with Azure: SQL Managed Instance, Cosmos DB, Storage Services, Azure Functions

4. Global project experience, and excellent communication skills, verbal and written, and soft skills in agile projects

SN Responsibility of / Expectations from the Role

1 Design and implement scalable and high-performance solutions using Azure Cosmos DB.

2 Develop data ingestion and transformation pipelines using PySpark and Azure Data Factory.

3 Optimize Cosmos DB performance through indexing, partitioning, and query tuning.

4 Collaborate with architects and data engineers to ensure best practices in data modeling and cloud architecture.

5 Implement and maintain CI/CD pipelines for automated deployments and testing.

6 Troubleshoot and resolve technical issues related to Cosmos DB and data pipelines.

Desirable Skills:

Keyword:

Skills: Digital : Python~Digital : Databricks~Digital : PySpark~Microsoft Fabric~MySQL

Experience Required: 8-10.

About the Role

You'll be at the forefront of designing and implementing robust data platform solutions that power advanced analytics, AI, and machine learning. Working with modern cloud technologies, you'll build scalable data foundations that enable clients to make smarter, data-driven decisions.

Key Responsibilities

• Build scalable data pipelines using Snowflake, AWS, GCP, and Databricks.
• Design and optimize data models for AI and machine learning workloads.
• Develop reliable data foundations for MLOps, governance, and data lineage.
• Integrate data from multiple sources into modern data platforms.
• Leverage Snowpark ML and Snowflake's native AI capabilities.
• Ensure data platforms are secure, scalable, and high-performing.

What We're Looking For

• 5+ years of hands-on experience with Snowflake.
• Strong proficiency in SQL and Python.
• Experience with AWS, Azure, or GCP.
• Knowledge of cloud storage services such as S3, ADLS, or GCS.
• Strong understanding of Dimensional Modeling and Data Vault.
• Experience with Scala or Java is a plus.

Tech Stack

• Data Warehouse: Snowflake
• Programming: SQL, Python, Scala (Good to Have), Java (Good to Have)
• Cloud: AWS, Azure, GCP
• Storage: S3, ADLS, GCS
• AI/ML: Snowpark ML, MLOps

Perks & Benefits

• Public Speaking & Communication Program
• Mentoring Program with Senior Support Leads
• 360° Progress Reviews
• Weekly Learning Sessions & Guilds
• Paid Certifications
• Hackathons & Innovation Days
• Recognition & Rewards Programs
• Team Socials & Annual Offsites
• Employee Assistance Program (24/7 Wellbeing Support)

The Data People Shaping Tomorrow

Our client helps organizations unlock the power of data through modern cloud, analytics, and AI solutions. We believe in creating an environment where talented technologists can learn, innovate, and make a real impact while building cutting-edge data platforms for global clients. If you're passionate about data engineering and want to work with the latest technologies in AI, cloud, and analytics, we'd love to hear from you.

Full-Stack Engineer (Backend Heavy)

Experience: 4–6 Years | Function: Engineering — Product | Location: On-site

About Us

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

About the Role

We are looking for a Full-Stack Engineer with a strong backend bias to help build end-to-end product experiences across Lumen and Agent Studio. You will own features from database and API design through to the front-end experience, working closely with product and design to ship AI-powered experiences that real business users depend on every day.

What You’ll Do

Design and build backend services and APIs in Python that power core product and AI-agent features.

Build front-end interfaces and experiences that let users interact naturally with AI agents, insights and CRM workflows.

Own features end-to-end — from data modeling and backend logic to UI implementation, testing and release.

Work with product managers and designers to translate requirements into well-architected, scalable systems.

Integrate with LLM-based and agentic backend systems built by the AI/ML engineering team.

Optimize application performance, reliability and code quality across the stack.

Engage directly with customers and customer success teams to understand workflows, triage issues and inform roadmap decisions.

What We’re Looking For

4–6 years of professional full-stack engineering experience, with a clear backend-heavy skill set in Python.

Strong experience designing and building REST/GraphQL APIs, data models and scalable backend services.

Working proficiency with modern front-end frameworks (e.g., React) to build and integrate user-facing features.

Experience with relational/NoSQL databases, caching and cloud infrastructure.

Ability to move fast in a zero-to-one environment while maintaining code quality and system reliability.

Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

Experience building features on top of LLM or AI-agent backends.

Prior experience in CRM, SaaS or enterprise business applications.

Exposure to real-time or voice-based product interfaces.

We need a senior, hands-on Ansible + Python automation expert to define automation standards, build scalable solutions, and act as the final technical authority for code quality and design. This is not just a developer role — it combines technical leadership, governance & standards ownership, and hands-on development.

We are looking for someone who has:

• Led or owned automation standards / frameworks
• Strong Ansible + Python development experience
• Experience reviewing/approving code or design
• Hands-on experience with CI/CD pipelines (GitHub Actions or similar)

We will not consider profiles with:

• Only scripting experience (no architectural/guidance role)
• No experience with Ansible at scale
• No exposure to code reviews / governance / standards
• Pure operations profiles without development depth

Ideal candidate positioning: Senior Automation Architect / Lead DevOps Engineer / Ansible Lead Developer

Interview mode: Face-to-Face only (mandatory)

Reporting: Day 1 reporting post offer, industrial sector site

Experience: 5+ Years

Employment Type: Full-Time

Role Overview

We are looking for an experienced GCP Data Engineer with 5+ years of experience in data engineering and strong hands-on expertise in Google BigQuery, Google Cloud Storage (GCS), Airflow/Cloud Composer, Python, and Vertex AI. The candidate should be capable of designing, developing, and maintaining scalable data pipelines and cloud-based data solutions on Google Cloud Platform.

Key Skills – Mandatory

• BigQuery – Strong hands-on experience in data warehousing, SQL, optimization, and performance tuning.
• Google Cloud Storage (GCS) – Experience with data storage, file management, and integration with data pipelines.
• Airflow / Cloud Composer – Experience in developing, scheduling, monitoring, and managing data workflows.
• Python – Strong programming skills for data engineering, ETL/ELT development, automation, and pipeline implementation.
• Vertex AI – Experience working with ML/AI workflows, model integration, or data pipelines supporting AI/ML solutions.

Good to Have / Added Advantage

• Dataproc – Experience with distributed data processing and Spark-based workloads.
• Cloud Data Fusion – Experience in building and managing data integration pipelines.
• Cloud Run – Understanding of deploying and running containerized applications/services on GCP.
• Experience with ETL/ELT processes and data pipeline development.
• Knowledge of GCP data architecture and cloud-native services.
• Experience in data quality, validation, monitoring, and troubleshooting.

Responsibilities

• Design, develop, and maintain scalable GCP-based data pipelines.
• Build and optimize data solutions using BigQuery and Cloud Storage.
• Develop and manage workflows using Airflow / Cloud Composer.
• Write efficient and reusable Python code for data processing and automation.
• Support Vertex AI integrations and AI/ML data workflows.
• Monitor pipeline performance and troubleshoot data processing issues.
• Work with cross-functional teams to understand data requirements and deliver reliable solutions.
• Implement best practices for data security, quality, scalability, and performance.

You must have :

• 5+ years of overall experience in Data Engineering.
• Strong hands-on experience with BigQuery, GCS, Airflow/Cloud Composer, Python, and Vertex AI.
• Strong understanding of data engineering concepts, ETL/ELT, data pipelines, and cloud technologies.
• Dataproc, Data Fusion, and Cloud Run experience will be an added advantage.

Title: AI/ML Test Engineer – GenAI

Location - Hyderabad

Experience - 1-3 years

Technical Skills -

• Strong experience in Generative AI, LLMs, and Agentic AI systems

• Hands-on expertise with AI evaluation frameworks (RAGAS, DeepEval, TruLens, LangSmith, Promptfoo, etc.)

• Proficiency in Python and AI/ML development libraries

• Knowledge of Prompt Engineering, prompt testing, and optimization

Ability to define and track evaluation metrics such as accuracy, relevance, groundedness, hallucination rate, latency, and user satisfaction

• Experience in creating automated evaluation pipelines and benchmarking frameworks

• Strong understanding of AI safety, guardrails, bias testing, and responsible AI practices

• Familiarity with REST APIs, JSON, vector databases, and knowledge retrieval systems

• Experience in A/B testing, human-in-the-loop evaluation, and red teaming

• Strong experience in Manual Testing of AI/GenAI applications, including functional, exploratory, UAT, regression, and end-to-end testing

• Expertise in validating Agent Reasoning, Tool Calling, Workflow Execution, and Response Quality

• Hands-on experience in Automation Testing using Python frameworks

Key Responsibilities -

• Design, execute, and automate evaluation strategies for Agentic AI applications.
• Develop evaluation datasets, test cases, and benchmark suites.
• Measure and improve agent performance, reasoning quality, tool usage, and workflow effectiveness.
• Analyze model outputs and identify hallucinations, biases, safety risks, and failure patterns.
• Collaborate with AI Engineers, Product Teams, and Domain Experts to improve agent quality and reliability.
• Generate evaluation reports, dashboards, and actionable recommendations.

About the Role

We are looking for a Full Stack AI Engineer who can take an ambiguous problem and turn it into a complete, production-ready AI product.

This is a builder role.

You will work across the entire stack — AI models, agents, backend services, APIs, databases, data pipelines, frontend applications, infrastructure, and production deployment. You should be comfortable deciding what needs to be built, writing the code, deploying it, measuring whether it works, and continuously improving it.

We are not looking for someone who only builds notebooks, trains models, writes prompts, or creates architecture diagrams for another team to implement. We want engineers who ship complete products.

A typical project might involve designing an agentic workflow, building a retrieval pipeline, writing Python APIs, creating a React interface, integrating enterprise data, deploying to Kubernetes, implementing evaluations, and debugging the application in production.

The distance between an idea and working software should be measured in weeks, not quarters.

This role is based in Hyderabad and is 6 days per week in the office.

We are looking for:

1. A person that can smoothly navigate extreme ambiguity
2. Full stack software builder
3. AI depth, must have built a production AI system
4. Excellent top-notch communication and stakeholder management
5. Prioritizes growth over work-life balance

What You'll Do

Build AI Products End-to-End

• Own AI applications from problem definition through architecture, development, deployment, and production operation.
• Translate ambiguous product and business requirements into working software.
• Build across AI/ML, backend services, APIs, databases, frontend interfaces, data pipelines, authentication, infrastructure, and observability.
• Rapidly prototype, test with real users and data, and turn successful ideas into production-grade systems.
• Make pragmatic engineering decisions based on speed, reliability, simplicity, maintainability, and user value.

AI, LLMs & Agents

• Build production applications using commercial and open-source foundation models.
• Design RAG systems, agentic workflows, tool/function calling, structured outputs, memory, human-in-the-loop workflows, and multi-agent systems where appropriate.
• Work with frameworks such as LangGraph, LangChain, Semantic Kernel, LlamaIndex, or equivalent tools.
• Build retrieval systems using embeddings, vector search, BM25, hybrid retrieval, reranking, metadata filtering, and knowledge graphs.
• Design prompt and context engineering strategies for complex workflows.
• Evaluate model choices based on accuracy, latency, reliability, security, and cost.
• Build automated evaluations and regression tests for AI behavior.
• Fine-tune or adapt models when prompting and retrieval are insufficient.

Backend, Frontend & Data

• Build production backend systems primarily in Python using FastAPI, Flask, Django, or similar frameworks.
• Design APIs, asynchronous workflows, background jobs, queues, caching layers, and event-driven systems.
• Work with PostgreSQL, SQL Server, MongoDB, Redis, Snowflake, and other production data stores.
• Build modern applications using React, Next.js, TypeScript, JavaScript, or equivalent frameworks.
• Create interfaces for copilots, conversational AI, workflow automation, analytics, review queues, and operational applications.
• Implement streaming responses, real-time updates, authentication, permissions, and API integrations.
• Build ingestion and transformation pipelines for structured and unstructured enterprise data.
• Work with documents, databases, APIs, event streams, images, logs, and operational datasets.
• Maintain provenance, permissions, metadata, and traceability across enterprise information.

ML & Computer Vision

• Use classical ML or deep learning when it is better suited to the problem than an LLM.
• Build systems involving classification, forecasting, anomaly detection, ranking, recommendations, optimization, or prediction.
• Build computer-vision applications involving detection, classification, segmentation, OCR, tracking, or image/video analysis.
• Work with PyTorch, TensorFlow, Hugging Face, OpenCV, or equivalent tools.
• Understand model development, evaluation, inference, and productionization.

Deploy & Operate What You Build

• Deploy applications across AWS, Azure, GCP, on-premises, hybrid, or edge environments.
• Containerize and operate applications using Docker and Kubernetes.
• Build CI/CD pipelines, automated testing, monitoring, and observability.
• Own reliability, latency, availability, security, evaluation, cost, and scalability.
• Debug failures across application code, AI models, data, infrastructure, and integrations.
• Build retries, fallbacks, rollback mechanisms, and human intervention into critical systems.

Integrate With Enterprise Systems

• Connect AI applications to enterprise platforms, databases, APIs, and operational systems.
• Integrate with systems such as ERP, MES, PLM, CRM, data warehouses, IoT platforms, document repositories, and legacy applications.
• Work within enterprise networking, security, and data-governance constraints.
• Implement authentication, authorization, secrets management, auditability, permissions, and data isolation.
• Build AI systems capable of safely operating on sensitive enterprise data.

What You Bring

• 5+ years of software engineering experience, with meaningful experience building AI/ML-powered products. Exceptional candidates with less experience but strong demonstrated ability will be considered.
• Strong hands-on programming ability in Python.
• Experience building complete production applications rather than isolated models, notebooks, or proofs of concept.
• Strong backend fundamentals including APIs, databases, distributed systems, and application architecture.
• Experience with React, Next.js, TypeScript, JavaScript, or equivalent frontend technologies.
• Strong understanding of LLMs, RAG, agents, tool calling, embeddings, vector search, prompt/context engineering, AI evaluation, and ML fundamentals.
• Experience with SQL and production databases.
• Experience with at least one major cloud platform: AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, or equivalent production infrastructure.
• Understanding of production AI concerns including reliability, latency, security, observability, evaluation, and cost.
• Strong debugging skills across the full stack.
• Ability to independently turn loosely defined requirements into working software.
• Strong product judgment, high agency, technical curiosity, and a bias toward shipping.
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent demonstrated experience.

Preferred / Top-Candidate Signals

• You've independently shipped an AI application from database → backend → AI → frontend → production.
• You've built production RAG or agentic systems, not just demos.
• You've used LangGraph, LangChain, Semantic Kernel, LlamaIndex, or similar frameworks.
• You understand when not to use an LLM or agent.
• You've worked with hybrid retrieval, reranking, vector search, or knowledge graphs.
• You've built with both commercial and open-source models.
• You've deployed ML or computer-vision systems into production.
• You have experience with React/Next.js + Python/FastAPI or a comparable modern stack.
• You have experience with Kubernetes, cloud infrastructure, and production observability.
• You have integrated software with complex enterprise or industrial systems.
• Experience in manufacturing, industrial, supply chain, logistics, engineering, energy, aerospace, automotive, or other physical-world environments is a strong plus.
• You've built meaningful side projects, open-source software, startups, or substantial systems outside your assigned responsibilities.
• You have a history of turning vague ideas into shipped products.

What Makes Someone Exceptional

The strongest engineers in this role combine three abilities:

AI Engineering — Choose the right model, retrieval approach, agent architecture, evaluation method, or ML technique.

Software Engineering — Build everything around the intelligence: frontend, backend, data, APIs, infrastructure, security, integrations, and deployment.

Product Judgment — Understand what actually needs to be built and rapidly turn it into something users can use.

A typical week might involve designing an agent workflow, writing FastAPI services, building a React interface, creating a retrieval pipeline, connecting enterprise data, deploying to Kubernetes, implementing evaluations, and debugging real-world behavior.

You should not need five different teams to turn an idea into a working product. You should be able to build.

Why This Role

• Build entire products, not isolated models or prototypes.
• Own the full stack: AI, backend, frontend, data, infrastructure, and deployment.
• Ship quickly: move from idea to working software in weeks.
• Work across modern AI: LLMs, agents, RAG, ML, computer vision, optimization, and enterprise data.
• Solve real-world problems: build software used in complex operational environments.
• See your work in production: own the path from first commit to real users.
• Compensation is flexible for exceptional candidates. 

Sr Backend Developer (Full Stack – Python / Django)

Preference: Please apply only if you are an IIT/NIT graduate and have strong hands-on experience in full-stack development with Python & Django.

Insurance/InsurTech experience is preferred. Strong engineering fundamentals and a willingness to learn the domain are more important.

Office location – Bangalore

Work mode – Onsite

Working Days – 5 days a week

Budget - 12-15 LPA

Work Experience - 2-5 years

Role Summary

We’re hiring Sr Backend Developers with strong full-stack Django expertise to own backend workstreams end-to-end and contribute to frontend development when needed. Hands-on Python/Django experience is essential.

(HTML, JavaScript, jQuery, CSS).

Key Responsibilities

 Design, build, and maintain scalable backend services and APIs for Fuse-OS

 Own medium-to-complex workstreams end-to-end: data models, APIs, background jobs, and light UI

wiring

 Improve reliability, performance, observability, and maintainability of production systems

 Apply sound engineering practices for multi-tenant SaaS (security, permissions, data isolation)

 Collaborate closely with frontend, QA, and product/delivery to ship high-quality releases

 Mentor other backend engineers through design discussions, pairing, and code reviews

 Participate in architecture discussions and help evolve platform technical standards

 Support production troubleshooting and continuous improvement of engineering quality

Required Skills & Qualifications

 Solid experience with Django REST Framework, asynchronous job processing (e.g., Celery), Redis, and

PostgreSQL

 Proven ability to design data models, write migrations, and ship maintainable APIs

 Full-stack capability: HTML, JavaScript, jQuery, and CSS sufficient to complete UI wiring without blocking

frontend

 Strong debugging skills across application, database, and background-job layers

 Experience collaborating in Agile teams with clear quality standards and delivery cadence

Preferred / Nice to Have

 Hands-on Selenium automation experience with Python (big plus)

 AWS familiarity (compute, storage, messaging, monitoring, IAM basics) — optional but strongly preferred

 Experience with multi-tenant architectures, containers, and production SaaS operations

 Exposure to document/data processing pipelines, reconciliation-style systems, or enterprise integrations

 Awareness of application security, RBAC, auditability, and privacy-by-design practices

 Interest in AI-assisted product workflows and intelligent automation

What We Offer

 Opportunity to build a category-defining Insurance Distribution Operating System (Fuse-OS)

 Work on modern multi-tenant SaaS architecture with meaningful ownership and mentoring

 Collaborative product and engineering culture focused on quality and customer outcomes

 Exposure to enterprise SaaS, AI-enabled workflows, and large-scale operational systems

Job Description – QA & Data Validation Engineer

Experience: 5–6 Years

Location: Pan India

Employment Type: Full-Time

Work Mode: Pan India / Remote or Hybrid as applicable

About the Role

We are looking for an experienced QA & Data Validation Engineer with 5–6 years of hands-on experience in data quality assurance, solution analysis, data validation, SQL, Python, PySpark, Azure Data Factory, Azure Synapse Analytics, and Power BI validation.

The ideal candidate will be responsible for validating large-scale data pipelines, performing source-to-target reconciliation, analyzing business rules, investigating data defects, and ensuring the accuracy, completeness, and consistency of data across source, staging, intermediate, and target systems.

The role requires strong analytical and problem-solving skills along with the ability to work closely with development, data engineering, business, and other stakeholders in an Agile delivery environment.

You will also contribute to the design, development, and maintenance of automated validation frameworks and utilities using Python, SQL, PySpark, Azure Data Factory, and Azure Synapse.

---

Key Responsibilities

1. QA & Solution Analysis

- Analyze business and technical requirements to understand data processing and validation needs.

- Participate in requirement analysis sessions and clarify functional and technical requirements with stakeholders.

- Review solution designs, data flows, mapping documents, interface specifications, and business rules.

- Validate that implemented solutions meet defined business and technical requirements.

- Identify gaps, inconsistencies, ambiguities, and potential data quality issues during requirement and solution analysis.

- Translate business requirements into detailed test scenarios, test cases, and validation conditions.

- Perform end-to-end validation of data processing workflows.

- Ensure data is accurately processed from source systems through intermediate layers to final outputs.

- Validate business rules and transformation logic implemented within data pipelines.

2. Test Planning & Execution

- Prepare comprehensive test strategies, test plans, test scenarios, and test cases for data-intensive applications.

- Execute functional, integration, regression, system, and data validation testing.

- Perform positive and negative testing for different data processing scenarios.

- Validate data pipelines across multiple environments, including staging, testing, and production.

- Identify test data requirements and prepare appropriate datasets for validation.

- Execute SQL queries to validate data processing and transformation results.

- Document test results, observations, defects, and validation evidence.

- Track testing progress and communicate status, risks, issues, and dependencies to stakeholders.

3. Data Validation & Reconciliation

- Perform detailed source-to-target data validation and reconciliation.

- Validate source, intermediate, staging, and output datasets.

- Perform record count validation between source and target systems.

- Verify data completeness, consistency, accuracy, and integrity.

- Validate data transformations against defined business rules.

- Perform field-level and record-level comparisons.

- Validate data types, formats, precision, scale, and null handling.

- Verify schema structure, layout, column names, and column sequence.

- Validate mandatory and optional fields.

- Identify missing, duplicate, truncated, or incorrectly transformed records.

- Analyze invalid records, rejected records, and exception datasets.

- Verify exception and reject-handling mechanisms.

- Compare production and staging data to identify discrepancies.

- Perform reconciliation between files, databases, and reporting layers.

- Validate data across different processing stages and identify the root cause of discrepancies.

4. File & Data Processing Validation

- Validate large-scale datasets across multiple file formats.

- Perform validation of:

 - CSV files

 - Delimited files

 - Fixed-width files

 - Excel files

 - Database tables

 - Structured and semi-structured datasets

- Validate file layouts, headers, delimiters, record formats, and column sequences.

- Verify file-level and record-level counts.

- Analyze source, intermediate, and final output files.

- Validate file-to-database and database-to-file reconciliation.

- Identify incomplete, corrupted, malformed, or invalid records.

- Verify data movement and transformation between different storage locations.

- Validate Azure-to-AWS file transfer processes.

- Ensure transferred files are complete and match the expected source datasets.

---

5. Defect Investigation & Root Cause Analysis

- Investigate data discrepancies and application/data pipeline defects.

- Perform detailed root cause analysis for data quality and validation failures.

- Analyze source data, transformation logic, pipeline execution, database records, and output datasets to identify defects.

- Collaborate with developers and data engineers to resolve identified issues.

- Reproduce defects and provide detailed technical evidence.

- Perform defect impact analysis.

- Conduct retesting and regression testing after defect resolution.

- Monitor recurring data quality issues and recommend preventive solutions.

- Maintain detailed defect documentation and validation results.

---

6. Python Development & Automation

- Develop Python scripts and utilities for data validation and reconciliation.

- Design, develop, and maintain reusable data validation frameworks.

- Automate repetitive data comparison and validation activities.

- Build automated utilities for:

 - Record count validation

 - Data completeness checks

 - Schema validation

 - Column sequence validation

 - Source-to-target comparison

 - Duplicate detection

 - Exception identification

 - Data quality checks

 - Automated reporting

- Develop Python-based validation and reporting utilities.

- Optimize Python scripts for processing large datasets.

- Maintain and enhance existing automation frameworks.

- Implement reusable validation components to improve testing efficiency and coverage.

---

7. SQL Development & Data Analysis

- Write complex SQL queries for data analysis and validation.

- Perform data extraction and comparison using SQL Server / SSMS.

- Validate source and target database records.

- Perform joins, aggregations, subqueries, CTEs, and analytical queries as required.

- Develop SQL queries to identify data mismatches, duplicates, missing records, and transformation issues.

- Validate database tables, schemas, columns, constraints, and relationships.

- Perform record count and reconciliation checks using SQL.

- Analyze SQL Server metrics databases.

- Validate data processing results against expected business rules.

- Troubleshoot data discrepancies using SQL queries.

---

8. PySpark & Large-Scale Data Processing

- Develop and execute PySpark notebooks for large-scale dataset processing and validation.

- Analyze large volumes of structured and semi-structured data.

- Perform data transformation and validation using PySpark.

- Compare large source and target datasets efficiently.

- Implement data quality and reconciliation checks using PySpark.

- Analyze exception, reject, and invalid datasets.

- Optimize data validation processes for large datasets.

- Work with Azure Synapse notebooks and data processing environments.

---

9. Azure Data Factory & Pipeline Testing

- Design and execute validation scenarios for Azure Data Factory (ADF) pipelines.

- Validate pipeline execution, data movement, transformations, and dependencies.

- Monitor pipeline runs and investigate failures.

- Validate source-to-target data movement through ADF.

- Develop and maintain test pipelines using Azure Data Factory.

- Verify pipeline parameters, triggers, activities, and execution results.

- Validate file ingestion and processing workflows.

- Perform end-to-end testing of data pipelines.

- Investigate pipeline-related data discrepancies and failures.

---

10. Azure Synapse Analytics

- Work with Azure Synapse Analytics for data validation and analysis.

- Develop and execute Synapse notebooks using PySpark.

- Validate datasets processed through Synapse pipelines and notebooks.

- Perform data quality and reconciliation checks within Synapse environments.

- Analyze large-scale datasets and processing results.

- Validate data movement between Azure storage, Synapse, databases, and reporting systems.

---

11. Azure Storage & Cosmos DB

- Validate data stored in Azure Storage Accounts and Containers.

- Verify file ingestion, processing, and output data.

- Perform file-level and content-level validation within Azure storage.

- Validate data processing workflows involving Azure Storage.

- Perform data validation in Azure Cosmos DB.

- Verify records, fields, formats, and data completeness within Cosmos DB.

- Investigate discrepancies between source files, Azure storage, databases, and Cosmos DB.

---

12. AWS S3 & Azure-to-AWS Validation

- Validate files stored in AWS S3.

- Perform source-to-target validation for files transferred between Azure and AWS.

- Verify file counts, file names, sizes, formats, and record counts.

- Compare source files with transferred S3 files.

- Validate data integrity after cloud-to-cloud file transfers.

- Investigate missing, incomplete, duplicate, or corrupted files.

- Support end-to-end validation of Azure-to-AWS data movement processes.

---

13. Metrics, Reporting & Power BI Validation

- Extract and validate source system metrics.

- Validate metrics stored in SQL Server databases.

- Perform reconciliation between source metrics, database metrics, and reporting outputs.

- Validate Power BI dashboards and reports against underlying source data.

- Verify report calculations, KPIs, measures, filters, and aggregations.

- Perform file-to-database-to-Power BI reconciliation.

- Validate data displayed in Power BI against SQL Server and source datasets.

- Identify discrepancies between backend data and dashboard results.

- Support reporting and analytics teams with data validation and troubleshooting.

---

14. Production Support & Job Monitoring

- Monitor scheduled data processing jobs and pipelines.

- Perform production validation and health checks.

- Analyze production failures and data discrepancies.

- Support incident investigation and resolution.

- Compare production and staging environments to identify differences.

- Validate production data after deployments and pipeline executions.

- Monitor ECG jobs and provide support for job execution and data processing issues.

- Perform post-production validation and reconciliation.

- Communicate critical production issues and risks to relevant stakeholders.

---

15. Agile Delivery & Stakeholder Collaboration

- Work effectively within an Agile/Scrum delivery environment.

- Participate in sprint planning, daily stand-ups, backlog refinement, sprint reviews, and retrospectives.

- Collaborate with Business Analysts, Developers, Data Engineers, DevOps teams, Product Owners, and other stakeholders.

- Provide timely updates on testing progress and issues.

- Participate in requirement clarification and solution discussions.

- Support release planning and production deployment activities.

- Track work items and defects using Rally.

- Ensure testing activities are aligned with sprint and release timelines.

---

Required Technical Skills

Mandatory Skills

- 5–6 years of experience in QA / Data Validation / Data Testing / Data Quality Engineering.

- Strong experience in SQL and data analysis.

- Hands-on experience with Python development and automation.

- Experience with PySpark and large-scale data processing.

- Strong experience with Azure Data Factory (ADF).

- Experience with Azure Synapse Analytics / Synapse Pipelines / Notebooks.

- Strong understanding of source-to-target data validation and reconciliation.

- Experience in data completeness, record count, schema, layout, and column validation.

- Experience in defect investigation and root cause analysis.

- Experience validating large datasets and multiple file formats.

- Experience with SQL Server / SSMS.

- Experience with Power BI dashboard/report validation.

- Strong understanding of data pipelines and ETL/ELT processes.

Cloud & Data Platform Experience

- Azure Data Factory

- Azure Synapse Analytics

- Azure Synapse Pipelines

- Azure Synapse Notebooks

- Azure Storage Accounts

- Azure Storage Containers

- Azure Cosmos DB

- Azure Privileged Identity Management (PIM)

- AWS S3

- Azure-to-AWS file transfer validation

---

Preferred Skills

- Experience developing automated data validation frameworks.

- Experience building automated reporting and reconciliation utilities.

- Knowledge of ETL/ELT testing methodologies.

- Experience working with very large datasets.

- Experience in production data validation and support.

- Knowledge of cloud-based data platforms.

- Experience with Power BI data reconciliation.

- Experience working in Agile environments.

- Experience with Rally or similar Agile project management tools.

- Familiarity with Microsoft Copilot and AI-assisted productivity/automation tools.

---

Key Responsibilities at a Glance

The successful candidate will be responsible for:

- Requirement analysis and clarification

- Business rule validation

- Test planning and execution

- Data quality and data validation

- Source-to-target reconciliation

- Record count and completeness validation

- Schema and layout validation

- Column sequence validation

- Exception and reject data analysis

- Production vs. staging comparison

- SQL-based data analysis

- Python automation

- PySpark development

- Azure Data Factory pipeline testing

- Azure Synapse validation

- Azure Storage validation

- Cosmos DB validation

- AWS S3 validation

- Azure-to-AWS file transfer validation

- Power BI dashboard validation

- SQL Server metrics validation

- Automated reporting

- Defect investigation and root cause analysis

- Production job monitoring and support

- Agile delivery and stakeholder collaboration

---

Candidate Profile

We are looking for a detail-oriented, analytical, and technically strong QA/Data Validation professional who can work independently on complex data validation assignments.

The candidate should be comfortable working with large datasets, writing SQL queries, developing Python automation, analyzing PySpark datasets, validating cloud-based data pipelines, and troubleshooting data discrepancies across multiple systems.

Strong communication and stakeholder management skills are essential, as the role requires regular collaboration with technical and business teams.

---

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field is preferred.

Experience

5–6 years of relevant professional experience in QA, Data Testing, Data Validation, ETL Testing, Data Quality, Data Engineering QA, or a similar role.

Location

Pan India

Employment Type

Full-Time

Keywords

QA Engineer, Data QA, Data Validation, Data Testing, ETL Testing, Data Quality, SQL, Python, PySpark, Azure Data Factory, ADF, Azure Synapse, Synapse Analytics, Synapse Pipelines, Azure Storage, Cosmos DB, AWS S3, Power BI, SQL Server, SSMS, Data Reconciliation, Source-to-Target Validation, Data Pipeline Testing, ETL QA, Automation Testing, Data Analytics, Root Cause Analysis, Agile, Rally, Cloud Data Testing, Data Engineering QA.

Hiring for Data Scientist / Senior Data Scientist

Exp : 4 - 12 yrs

Edu : BE/B.tech/MCA

Work Location : Pune

Notice Period : Immediate - 15 days

Skills :

4+ years of experience in data engineering, data science, or related domains.

Hands-on experience with SQL, Python, and distributed data systems.

Knowledge of machine learning techniques and statistical analysis.

Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).

Familiarity with DevOps practices and CI/CD for data pipelines.

Platforms & Operations Experience (Preferred)

- Experience working with Azure, AWS, or Google Cloud data tools.

Operational experience with data orchestration tools (Airflow, ADF, Glue).

Understanding of Kubernetes, Docker, or containerized environments.

Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).

Experience in monitoring, logging, and alerting operations for data workflows.

SRE / Success Engineering role focused on production operations, reliability, AWS infrastructure, monitoring, incident management, and platform support for the ZT platform.

Core responsibilities include:

• Production monitoring and debugging of live systems.
• Incident investigation, troubleshooting, and problem resolution.
• AWS cloud infrastructure support and maintenance.
• Deployment and operational support activities.
• Supporting a 24x7 production environment.
• Working with GitHub-based development workflows.
• Technical debt remediation and platform improvements.
• Customer issue investigation and support.
• Security and compliance-related work, including FedRAMP initiatives.

Preferred Skills:

AWS (especially S3 and EC2)

Strong debugging and troubleshooting skills

Site Reliability Engineering (SRE) experience

GitHub experience

Basic software development skills

TypeScript/JavaScript knowledge

C# preferred

AI experience is a plus.

Candidate should be a hands-on engineer with strong AWS, SRE, operational ownership, production support, and debugging capabilities, rather than a pure application or full-stack developer.

EMBEDDED AI ENGINEERING POD

AI Implementation Engineer Role

Level: AI Implementation Engineer Senior / Advanced - 6+ years

Practice: Wissen GenAI

Locations: Mumbai / Bengaluru / New York - hybrid, embedded with delivery teams

Reports to: EMBEDDED AI PRACTICE Senior AI Engineering Specialist (Architect); Wissen GenAI Program Lead

Embedded inside enterprise delivery teams, you work closely with global, cross-regional teams to turn prioritized GenAI use cases into production software - building, integrating, and hardening Azure-based AI solutions and accelerating adoption within the teams you join.

You deliver production software and help the teams you join work faster.

As an embedded AI Implementation Engineer, you help convert prioritized use cases into shipped, governed, measurable software.

Key responsibilities

1. Build and ship.

Implement GenAI features end to end on Azure - RAG pipelines, agents, APIs, and UI integrations - against enterprise systems and data.

2. Embed and enable.

Work inside the delivery pods: pair with their engineers, remove blockers, and transfer GenAI skills so adoption sticks after you move on.

3. Productionize.

Add evaluation, observability, guardrails, caching, and CI/CD so prototypes become reliable, cost-efficient services.

4. Integrate securely.

Connect to enterprise data with correct access control, secrets management, and compliance with enterprise security standards and handling of sensitive data.

5. Iterate on quality.

Use evaluation results and user feedback to improve grounding, accuracy, latency, and cost.

6. Measure.

Track delivery and quality metrics that roll up to the program's targets.

Must-have qualifications

• 6+ years in software engineering, with 2+ years building GenAI/LLM applications in production.
• Strong Python (incl. async) and Java (the primary enterprise application stack; Spring a plus); solid API and systems design.
• Azure GenAI hands-on: Azure OpenAI, Azure AI Foundry, Azure AI Search for RAG, Azure AI Document Intelligence (IDP), and Prompt Flow.
• Agent frameworks: Microsoft Agent Framework / Semantic Kernel / AutoGen (or LangChain / LangGraph) and tool / function calling.

Preferred

• RAG fundamentals: embeddings, chunking, vector search, reranking, and grounding.
• Data platforms: Snowflake including Cortex AI (Cortex Search, LLM functions) and SQL, for accessing and grounding on enterprise data.
• Prompt engineering as versioned code; building and running evaluations.
• DevOps: Azure DevOps / GitHub Actions, Docker, AKS / Azure Functions, and observability.
• Financial services or other regulated environments.
• Front-end (React) for AI-assisted UX; streaming and token level operations.
• Azure AI Content Safety and responsible-AI practices.
• Certification: Azure AI Engineer Associate.

What success looks like - first 6 to 12 months

• Multiple GenAI features shipped to production within the embedded delivery pods.
• Measurable adoption and productivity uplift in the teams you support.
• Reusable components adopted from the architects' reference framework.
• Clear contribution to faster time-to-market and lower defect rates.

GEMBA CONCEPTS

Experience: ~3–5 years Type: Full-time

AI/ML Engineer

Location: Bengaluru, India (Hybrid)

About Gemba Concepts

Gemba Concepts is a lean manufacturing and technology consulting firm helping clients across pharma, manufacturing, and logistics

modernize how they operate. We build production systems that sit close to the shop floor — warehouse management, manufacturing

traceability, and an applied AI/ML platform whose flagship use cases are visual quality inspection and predictive maintenance. We’re a

tight engineering team that ships real systems for demanding, often regulated, environments.

The Role

We’re looking for an AI/ML Engineer to take ML capabilities from prototype to production. You’ll own models end-to-end — framing the

problem with stakeholders, building and validating the model, and deploying it as a reliable service that holds up against real-world, messy

industrial data. This is a hands-on building role, not a pure research seat: your work goes into client-facing systems.

What You’ll Do

Build and ship computer vision models for visual quality inspection (defect detection, classification, segmentation) that perform under

real factory lighting, throughput, and edge-case conditions.

Develop predictive maintenance models using sensor/time-series data — anomaly detection, remaining-useful-life estimation, failure

prediction.

Own the full ML lifecycle: data pipelines, feature engineering, training, evaluation, and deployment, with proper versioning and monitoring.

Deploy and serve models in production on Azure (AKS), and keep them healthy — track drift, retraining triggers, and latency.

Integrate LLM-based capabilities (we use the Claude API and self-hosted open models) into delivery and product workflows where they

add leverage.

Collaborate with product, engineering, and domain experts to translate fuzzy operational problems into well-scoped ML solutions — and to

know when ML is not the right answer.

Communicate results and limitations clearly to non-ML stakeholders, including clients.

What We’re Looking For

3–5 years of hands-on experience building and deploying ML models in production (not just notebooks or coursework).

Strong Python and the modern ML stack — PyTorch or TensorFlow, scikit-learn, NumPy/Pandas.

Solid grounding in at least one of: computer vision (CNNs, object detection/segmentation, image preprocessing) or time-series /

anomaly detection.

Practical MLOps experience: containerization (Docker), model serving, experiment tracking, and deploying on a cloud platform — Azure /

Kubernetes (AKS) is a strong plus.

Comfort working with imperfect, real-world data — labeling strategy, class imbalance, data drift, and validation that reflects production

reality.

Good engineering hygiene (Git, testing, code review) and the ability to write code others can build on.

Nice to Have

Experience with industrial / manufacturing data or regulated environments (pharma, 21 CFR Part 11 awareness).

Hands-on LLM integration experience — RAG, prompt engineering, working with APIs or self-hosted models (vLLM, Qwen, etc.).

Edge deployment experience (running CV models on-device / near the line).

Exposure to data pipeline tooling and orchestration.

What You’ll Get

Real ownership of ML systems that go into production for serious clients.

A lean, senior-heavy team where you ship fast and learn across the stack.

Direct exposure to applied AI in manufacturing — a domain where the work has tangible, physical impact

GEMBA CONCEPTS

Experience: ~3–5 years Type: Full-time

AI/ML Engineer

Location: Bengaluru, India (Hybrid)

About Gemba Concepts

Gemba Concepts is a lean manufacturing and technology consulting firm helping clients across pharma, manufacturing, and logistics

modernize how they operate. We build production systems that sit close to the shop floor — warehouse management, manufacturing

traceability, and an applied AI/ML platform whose flagship use cases are visual quality inspection and predictive maintenance. We’re a

tight engineering team that ships real systems for demanding, often regulated, environments.

The Role

We’re looking for an AI/ML Engineer to take ML capabilities from prototype to production. You’ll own models end-to-end — framing the

problem with stakeholders, building and validating the model, and deploying it as a reliable service that holds up against real-world, messy

industrial data. This is a hands-on building role, not a pure research seat: your work goes into client-facing systems.

What You’ll Do

Build and ship computer vision models for visual quality inspection (defect detection, classification, segmentation) that perform under

real factory lighting, throughput, and edge-case conditions.

Develop predictive maintenance models using sensor/time-series data — anomaly detection, remaining-useful-life estimation, failure

prediction.

Own the full ML lifecycle: data pipelines, feature engineering, training, evaluation, and deployment, with proper versioning and monitoring.

Deploy and serve models in production on Azure (AKS), and keep them healthy — track drift, retraining triggers, and latency.

Integrate LLM-based capabilities (we use the Claude API and self-hosted open models) into delivery and product workflows where they

add leverage.

Collaborate with product, engineering, and domain experts to translate fuzzy operational problems into well-scoped ML solutions — and to

know when ML is not the right answer.

Communicate results and limitations clearly to non-ML stakeholders, including clients.

What We’re Looking For

3–5 years of hands-on experience building and deploying ML models in production (not just notebooks or coursework).

Strong Python and the modern ML stack — PyTorch or TensorFlow, scikit-learn, NumPy/Pandas.

Solid grounding in at least one of: computer vision (CNNs, object detection/segmentation, image preprocessing) or time-series /

anomaly detection.

Practical MLOps experience: containerization (Docker), model serving, experiment tracking, and deploying on a cloud platform — Azure /

Kubernetes (AKS) is a strong plus.

Comfort working with imperfect, real-world data — labeling strategy, class imbalance, data drift, and validation that reflects production

reality.

Good engineering hygiene (Git, testing, code review) and the ability to write code others can build on.

Nice to Have

Experience with industrial / manufacturing data or regulated environments (pharma, 21 CFR Part 11 awareness).

Hands-on LLM integration experience — RAG, prompt engineering, working with APIs or self-hosted models (vLLM, Qwen, etc.).

Edge deployment experience (running CV models on-device / near the line).

Exposure to data pipeline tooling and orchestration.

What You’ll Get

Real ownership of ML systems that go into production for serious clients.

A lean, senior-heavy team where you ship fast and learn across the stack.

• Direct exposure to applied AI in manufacturing — a domain where the work has tangible, physical impact

Role Overview

We are looking for a Junior AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations.

This role offers an opportunity to work closely with experienced engineers, product teams, and AI specialists on real AI-powered systems that support learners, educators, schools, and internal business operations.

At GoSuper EdTech, our cloud infrastructure is built on Google Cloud Platform — GCP. You will get hands-on exposure to GCP-based systems, backend services, AI integrations, deployment workflows, monitoring, cloud storage, databases, and automation pipelines.

You will help design, integrate, test, monitor, and maintain AI-enabled systems using modern tools such as AI APIs, LLMs, automation workflows, backend services, databases, GCP services, cloud deployment tools, and monitoring systems.

This role is ideal if you are curious about AI, comfortable with technical problem-solving, and interested in building reliable systems that connect software, data, cloud infrastructure, automation, and intelligent workflows.

What You’ll Do

• Support the development and maintenance of AI-powered systems, tools, and workflows.
• Assist in integrating AI APIs, LLM platforms, automation tools, and backend services into GoSuper products.
• Work with OpenAI, Gemini, Claude, or similar AI platforms under the guidance of senior engineers.
• Support AI and backend workflows deployed on Google Cloud Platform — GCP.
• Assist with GCP-based services such as Cloud Run, Compute Engine, Cloud Functions, Cloud Storage, Firebase, Firestore, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, and Cloud Monitoring, based on project needs.
• Help build AI workflows for content generation, chatbot systems, smart recommendations, internal automation, and productivity tools.
• Support backend integrations using Node.js, Python, REST APIs, webhooks, and third-party services.
• Assist in designing and maintaining system workflows that connect databases, applications, AI models, cloud services, and business tools.
• Work with databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or similar platforms.
• Help test AI outputs, validate workflows, debug issues, and improve system reliability.
• Monitor system performance, API usage, errors, logs, workflow failures, and cloud service health.
• Support deployment, configuration, and maintenance of AI-enabled product features on GCP.
• Collaborate with product managers, developers, designers, QA teams, and business teams to understand requirements and deliver working solutions.
• Participate in daily standups, sprint planning, technical discussions, and team meetings.
• Document AI workflows, system logic, API integrations, prompts, GCP configurations, deployment steps, and troubleshooting processes.
• Continuously learn and apply best practices in AI systems, backend engineering, automation, GCP cloud infrastructure, and production support.

What We’re Looking For

• 6 months to 1 year of experience in AI systems, backend development, software engineering, automation, DevOps support, cloud support, system integration, or relevant internship/project experience.
• Basic understanding of AI tools, LLMs, APIs, automation workflows, and software systems.
• Working knowledge of JavaScript, TypeScript, or Python.
• Basic backend development experience with Node.js, Express, NestJS, FastAPI, or similar frameworks.
• Basic understanding of Google Cloud Platform — GCP or willingness to learn GCP-based deployment and monitoring workflows.
• Understanding of REST APIs, webhooks, third-party integrations, and data flow between systems.
• Interest in AI APIs, prompt workflows, chatbot systems, automation tools, and intelligent product features.
• Basic understanding of databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or Redis.
• Ability to debug technical issues across APIs, workflows, logs, backend services, and cloud deployments.
• Good analytical thinking and problem-solving ability.
• Ability to write clear documentation for workflows, integrations, cloud configurations, and technical processes.
• Eagerness to learn new tools, AI platforms, system design concepts, GCP services, and cloud technologies.
• Good communication skills to work with technical and non-technical teams.
• Ownership mindset and willingness to take responsibility for assigned tasks.
• Comfortable working in a fast-paced startup environment.

Nice to Have

• Familiarity with AI APIs such as OpenAI, Gemini, Claude, or similar platforms.
• Basic understanding of prompt engineering and LLM-based workflows.
• Exposure to LangChain, LlamaIndex, embeddings, vector databases, or retrieval-augmented generation.
• Basic experience with GCP services such as Cloud Run, Cloud Functions, Firebase, Firestore, Cloud Storage, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, or Cloud Monitoring.
• Exposure to Google AI tools, Vertex AI, Gemini API, or AI-related services on GCP.
• Experience with automation tools, workflow builders, webhooks, or integration platforms.
• Exposure to Docker, CI/CD pipelines, GitHub Actions, deployment workflows, or cloud-based release processes.
• Experience working with logs, monitoring tools, API testing tools, or debugging platforms.
• Familiarity with Postman, Git, GitHub, Notion, Zoho, Slack, or similar productivity tools.
• Experience building chatbots, AI assistants, internal tools, or automated workflows.
• Personal, academic, internship, or open-source projects related to AI, automation, backend systems, GCP, or cloud tools.
• Interest in SaaS, EdTech, AI-powered products, and startup environments.

What You’ll Gain

• Hands-on experience building AI-powered systems in a real startup environment.
• Practical exposure to AI APIs, LLM workflows, automation systems, backend services, and GCP cloud infrastructure.
• Mentorship from senior engineers and product leaders.
• Experience working across AI, backend engineering, databases, APIs, integrations, deployment, system monitoring, and cloud operations.
• Opportunity to contribute to real product features used by learners, educators, schools, and institutions.
• Exposure to SaaS product development, EdTech workflows, AI-driven business solutions, and GCP-based production systems.
• Learning culture that encourages experimentation, feedback, and continuous improvement.
• Opportunity to understand how AI systems are designed, deployed, monitored, scaled, and improved in production.
• Access to Cult Elite and Cult Play Pass, offering wellness and lifestyle benefits to keep you energized and inspired.

Compensation

• Competitive salary with performance-based bonuses.
• Equity ownership through ESOPs — own a piece of the company you help build.
• Flexible remote work options with occasional Bengaluru office meetups.
• Health and wellness perks, including Cult Elite membership and Cult Play Pass for employees.
• Learning and development support to help you grow in AI systems, backend engineering, automation, SaaS, and GCP cloud technologies.
• Team retreats, virtual hangouts, and a collaborative work culture.

We are looking for a AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations. Apply in https://gosuperedtech.com/career/ai-system-engineer

About the role

We are building AI systems that read, understand and act on real business documents, bank statements, financial reports, policy documents and forms and putting them into production where accuracy and cost both matters.

This is not a research role and it is not a prompt-writing role. You will own features end to end: pick and deploy open-source models, build the pipelines around them, measure whether they actually work on our documents, drive the cost per document down, and keep the whole thing running in production.

You will work closely with the engineering and product teams, and your work will be directly used by business users from day one.

What you will do

Deploy and evaluate open-source models

• Select, deploy and benchmark open-source LLMs and vision-language models for specific, narrow use cases not general chat.
• Build evaluation sets from real documents and define what "good" means numerically (field-level accuracy, extraction recall, hallucination rate) before shipping.
• Run structured comparisons between models and approaches, and write up the trade-offs so the team can make a decision.
• Apply quantization, batching and other optimizations to fit models into a sensible GPU budget.

Build and optimize AI orchestration

• Design multi-step pipelines that combine deterministic code, ML models and LLM calls and know when not to use an LLM.
• Optimize for latency, cost and reliability: caching, batching, request routing, fallback tiers, retries and graceful degradation.
• Instrument pipelines so failures are visible and traceable rather than silent.

Ship to production

• Package models and services with Docker, expose them behind clean APIs, and deploy them to our GPU and CPU infrastructure.
• Handle the unglamorous production concerns: cold starts, timeouts, concurrency limits, versioning, rollback and monitoring.
• Own on-call-style responsibility for the AI features you build, including cost tracking.

Must-have skills

Programming & engineering

• Strong Python: type hints, async/await, dataclasses/Pydantic, clean module design, testing.
• REST API development with FastAPI (or Flask/Django with a willingness to move to FastAPI).
• Git, code review discipline, and the ability to write code someone else can maintain.
• Comfortable in Linux and on the command line.

Machine learning fundamentals

• Working knowledge of PyTorch and the Hugging Face ecosystem (transformers, tokenizers, accelerate).
• Understanding of inference-time concepts: tokenization, context windows, batching, precision (FP16/BF16/INT8), memory footprint.
• Ability to read a model card and a paper well enough to judge whether a model fits a use case.

Document processing

• Hands-on experience with at least two of: pypdfium2, PyMuPDF, pdfplumber, pdfminer.six, Docling, Unstructured, Surya, DocTR, LayoutLM family.
• Practical OCR experience (Tesseract, PaddleOCR, or a cloud OCR) and an understanding of when OCR is the wrong tool.
• Experience extracting tables from PDFs and dealing with merged cells, multi-line rows, and inconsistent column layouts.

Strongly preferred

You will be a much stronger candidate with any of these. We do not expect all of them.

Model serving & optimization

• vLLM, TGI, Ollama, llama.cpp, or Triton Inference Server.
• Quantization formats and tooling: GGUF, AWQ, GPTQ, bitsandbytes, ONNX Runtime, INT8 export.
• Serverless GPU platforms: Modal, RunPod, Replicate, Baseten including cold-start and container-lifecycle management.
• LoRA / QLoRA fine-tuning with PEFT for narrow, task-specific improvements.

Vision-language models

• Practical use of open VLMs: Qwen2.5-VL, InternVL, Granite Vision, Molmo, Phi-Vision, or similar.
• Awareness of where VLMs hallucinate especially on numeric and financial content and patterns for constraining them (using the model for layout only, sourcing values from the text layer, constrained decoding).

Orchestration & pipelines

• Workflow orchestration: Dagster, Airflow, Prefect, or Temporal.
• Async job patterns: Celery, RQ, or platform-native spawn/poll patterns.
• LLM orchestration frameworks (LangGraph, LlamaIndex, Haystack) with the judgement to know when plain Python is a better answer.
• Structured output enforcement: Instructor, Outlines, XGrammar, JSON schema / tool-use modes.

Evaluation & observability

• Building golden datasets and regression suites for extraction tasks.
• Eval tooling: promptfoo, DeepEval, Ragas, or in-house harnesses.
• LLM tracing and monitoring: Langfuse, Arize Phoenix, LangSmith, OpenTelemetry.

Nice extras

• Rule engines and policy evaluation (Open Policy Agent / Rego, Drools, rule-engine).
• Experience in fintech, lending, insurance or accounting documents.
• Handling of PII and data-security practices in document pipelines.
• Contributions to open-source ML or document-processing projects.

Why join us

• Real production ownership from month one your work goes to actual users, not a demo.
• Genuinely hard technical problems in document AI, not wrappers over an API.
• Small team, short decision cycles, direct access to leadership.
• Budget and freedom to evaluate and adopt new open-source models as they land.

To apply: send your CV along with a short note on one AI system you have taken to production what it did, what the accuracy was, and what broke.

Are you looking to work in the cutting edge area of applying data-science to help global customers get a better insight into their health? If so, read on and apply.

Role Name: Senior Data Scientist

Science Team | Full-Time | In-Office | Bangalore

The Role

The Ultrahuman Science Team builds the algorithms behind the Ring, M1 CGM, blood and urine biomarkers, and Performance Lab assessments. We are hiring a Senior Data Scientist to own those algorithms end to end: from the raw sensor signal to a model that is shipped, monitored, and trusted in users' hands.

This is a build role with real scope. In a typical month you will improve a production algorithm, root-cause a metric users are complaining about, and stand up the data pipeline the next model needs. The common thread is ownership: you take a vague question and return a working answer, without waiting to be handed scope.

What You'll Do

·      Own algorithms end to end: sleep staging, activity detection, sensor-derived metrics, and health scores. You frame the problem, build the features, train and evaluate the model, and see it live

·      Ship models, not notebooks: you prove a change on our own cohort before it reaches users, and a model is done only when it runs in production and you can tell how it is behaving

·      Validate against reference standards: design evaluations against gold standards, reference devices, and study ground truth, and know when a result is real and when it is an artifact

·      Own the data layer: cohort extraction, feature pipelines, study data, and raw sensor data, so the next model starts from clean inputs

What This Looks Like in Practice

1. Improving production algorithms - Take an existing production model like sleep staging, root-cause the failure modes against reference data, and ship a fix you can defend with numbers.

2. Building new models - Train an activity classifier on raw sensor data, design the labeled data collection that expands it, and pick the operating point so false positives never erode trust.

3. Proving it before it ships - Run a new steps algorithm against reference-device cohorts, decide with data when it is ready, and monitor how it behaves after rollout.

Who You Are

The two things we can't coach

·      High ownership, end to end: you take a problem from a vague question to a shipped model without waiting to be handed scope, and you can point to something you owned from raw data all the way to production

·      Hungry for more scope: you have outgrown your current role and want problems biggerthan your title, with the technical depth to be trusted with them

Also important

·      You've worked with human health data: wearables, physiological signals, or clinical data.

If your experience is close but not exact, show us why you will ramp fast

·      You've built at a startup: or somewhere small enough that nobody handed you clean data, clear specs, or a mature ML platform

·      You work like it's 2026: coding agents and AI tooling are part of how you build every day, and you can tell which new capabilities are worth adopting

·      You communicate: you can explain a model and its limits to a product manager, an engineer, or a founder, and hold your own with our scientists Core Technical Skills

·      Languages and data: Python and SQL daily, comfortable working in a real codebase

·      Machine learning: PyTorch or TensorFlow, scikit-learn, and gradient boosting, with the judgment to know which the problem needs

·      Advanced machine learning: time series and sequence models, deep learning on continuous physiological signals, and ensembles

·      Statistics and evaluation: hypothesis testing, experiment and A/B design, model evaluation, and error analysis against a reference standard

·      Scale and cloud: Spark or equivalent on large datasets, and AWS, GCP, or Azure

·      Production ML and MLOps: training pipelines, model versioning, deployment, monitoring, and drift detection

·      LLMs and agentic systems: fine-tuning and serving models, building agentic pipelines, and using coding agents to move faster

Experience:

- 4 to 5 years building and shipping machine learning systems. We index on what you have shipped and on trajectory, not the exact number of years; if you are a little earlier but have clearly outgrown your current scope, we want to hear from you.

- Bachelor's or higher in engineering, computer science, statistics, or a related field.

How We Work and Who Thrives Here

- The Science team is small and moves fast, and much of the work has no precedent to copy.

- People do their best work here when they are energized by ambiguity, low on ego, quick to adopt a better idea no matter where it comes from, and comfortable owning something before anyone has told them how. If you need a mature data org, clean labelled datasets, and clear guardrails to thrive, this particular role will not be the right fit, and that is worth knowing up front.

What You'll Gain

·      Ownership of algorithms that hundreds of thousands of people see every morning

·      A dataset most scientists never get to touch: 100M+ nights of sleep and continuous physiological signals at scale

·      Direct collaboration with the engineering, product, and design teams building Ultrahuman

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Get to Know Us:

At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.

Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, India, and Singapore. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information. 

If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

Job application link : https://grnh.se/z7qx2ehx1us