50+ Python Jobs in India

Job Title : Senior Data Engineer – Databricks

Experience : 14 to 20 Years

Location : HSR Layout, Bangalore

Work Mode : Hybrid – 3 Days WFO

Shift : 11:30 AM – 07:30 PM IST

Positions : 2

Notice Period : Immediate Joiners Only

Interview : 1 Technical Round + 2 Client Rounds

Role Overview :

We are looking for a Senior Data Engineer to build and lead enterprise-scale data platforms for a Switzerland-based commodity client.

The role requires a strong hands-on Data Engineering professional with expertise in Databricks, PySpark, Python, SQL, and AWS, along with technical leadership and stakeholder management experience.

Must-Have Skills :

• 14 to 20 years of Data Engineering experience
• Databricks & Apache Spark / PySpark
• Python & SQL
• AWS Cloud
• Lakehouse Architecture
• ETL / ELT & Distributed Data Processing
• Batch & Streaming Pipelines
• Data Pipeline Optimization & Data Modeling
• CDC & Incremental Processing
• Git, CI/CD & Testing
• Data Quality, Monitoring & Observability
• Technical Leadership & Stakeholder Management

Key Responsibilities :

• Design and build scalable data pipelines using Databricks, PySpark, Python, SQL, and AWS.
• Own data products from design through production.
• Develop batch / streaming pipelines and reusable ETL / ELT frameworks.
• Optimize pipelines for performance, scalability, reliability, and cost.
• Design scalable data architectures and data models.
• Implement data quality, monitoring, lineage, and CI/CD practices.
• Lead technical discussions and mentor engineering teams.
• Collaborate with business stakeholders, architects, product owners, and engineering teams.
• Remain hands-on while providing technical leadership.

Ideal Candidate :

A 14 to 20 years experienced, hands-on Data Engineering leader with strong Databricks + PySpark + AWS expertise, excellent communication, stakeholder management, and experience delivering enterprise-scale data platforms.

🔴 Super Urgent : Only Bangalore-based immediate joiners.

About NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description

We are looking for a passionate and experienced Backend Engineer (Python) to join our engineering team. The ideal candidate will have strong expertise in backend development, API design, scalable application architecture, and SaaS applications, along with familiarity with React and frontend technologies. You will collaborate with cross-functional teams to build, enhance, and maintain robust, secure, and high-performance applications.

Roles and Responsibilities

• Design, develop, and maintain scalable and high-performance web applications and backend services
• Develop secure, efficient, and reliable backend services and RESTful APIs using Python
• Design and implement scalable microservices and distributed application components
• Collaborate with frontend engineers and contribute to React-based features or integrations when required
• Work closely with product managers, designers, QA engineers, and other stakeholders to deliver high-quality features
• Write clean, maintainable, reusable, and testable code following software engineering best practices
• Participate in code reviews and contribute to coding standards, engineering practices, and technical improvements
• Optimize applications, APIs, databases, and backend services for performance, reliability, and scalability
• Troubleshoot, diagnose, and resolve application and production issues
• Contribute to system architecture, technical design decisions, and continuous improvement initiatives
• Develop and maintain automated tests to ensure application quality and reliability
• Collaborate with DevOps teams to support CI/CD pipelines, containerized deployments, and cloud-based applications

Requirements

• 3 to 6 years of professional experience in Backend Development using Python
• Strong hands-on experience with Python backend frameworks such as Django and Flask
• Experience building and supporting SaaS applications, with exposure to microservices, caching, pub-sub, messaging technologies, RESTful APIs, and distributed systems
• Strong understanding of databases such as PostgreSQL, MySQL, MongoDB, or SQL Server
• Experience with version control systems such as Git
• Exposure to technologies such as Kafka, Redis, Elasticsearch, Redshift, Nginx, and GraphQL is a plus
• Strong foundation in computer science, including data structures, algorithms, object-oriented programming, and software design principles
• Familiarity with CI/CD pipelines and tools such as Jenkins.
• Good understanding of cloud platforms such as AWS, Azure, or GCP
• Strong understanding of software design principles, scalable application architecture, and data structures
• Experience with containerization technologies such as Docker.
• Knowledge of automated testing frameworks and best practices.
• Experience working in Agile/Scrum environments
• Familiarity with frontend technologies, particularly React
• Strong problem-solving, analytical, communication, and collaboration skills

Why Join Us?

• Opportunity to work on a cutting-edge healthcare product
• A collaborative and learning-driven environment
• Exposure to AI and software engineering innovations
• Excellent work ethic and culture

If you're passionate about technology and want to work on impactful projects, we'd love to hear from you!

About the Company

Fluxsolve Technovations Private Limited (incorporated 2023) builds Fuse-OS — an AI-powered Insurance Distribution Operating System. Fuse-OS is a unified enterprise platform that orchestrates people, processes, and insurance ecosystems across the distribution chain, from lead generation and policy issuance through servicing, reconciliation, payouts, compliance, and business intelligence.

Unlike traditional policy administration tools or point-solution workflow software, Fuse-OS serves insurers, brokers, corporate agents, aggregators, NBFCs, banks, automotive finance companies, OEMs, and dealer networks through three flagship platforms: Insurance Distribution Management, Revenue & Reporting Management, and Embedded & Group Products Management. The platform is cloud-native and AI-native, multi-tenant and modular, with enterprise security controls, configurable business rules, and integration-ready architecture.

About the Founders

Pankaj Sharma — Co-Founder & CEO. IIT Roorkee (B.Tech ECE). Leadership experience across insurance distribution and strategy, including roles at Angel One, Liberty General Insurance, Pasarpolis Indonesia, HDFC ERGO, and Coverfox, along with prior founding experience.

Prenit Wankhede — Co-Founder & CTO. IIT Kanpur (B.Tech + M.Tech EE). Engineering leadership across insurance technology and financial services, including roles at Liberty General Insurance, Morgan Stanley, and Coverfox, along with prior founding experience as CTO.

Role Summary

We are hiring Backend Developers with a full-stack orientation to help build and maintain Fuse-OS. You will primarily work with Python and Django, contribute to APIs and backend services, and comfortably support light frontend work using HTML, JavaScript, jQuery, and CSS. You will learn from senior engineers while delivering reliable features in a multi-tenant SaaS environment.

Key Responsibilities

·      Develop and maintain backend features using Python and Django

·      Build and enhance REST APIs, data models, business logic, and admin tooling

·      Work with relational databases (PostgreSQL) and background job processing patterns

·      Support full-stack contributions using HTML, JavaScript, jQuery, and CSS where needed

·      Write clean, testable code; participate in code reviews and follow team engineering standards

·      Debug issues across application, data, and service layers with guidance from senior engineers

·      Collaborate with frontend, QA, and product/delivery stakeholders on requirements and delivery quality

·      Contribute to technical documentation and knowledge sharing within the team

Required Skills & Qualifications

·      Hands-on experience with Python and Django (academic projects, internships, or professional work)

·      Working knowledge of PostgreSQL / relational data modeling and ORM usage

·      Comfort with Git, Linux basics, and debugging application behavior from logs

·      Frontend familiarity for full-stack contribution: HTML, JavaScript, jQuery, and CSS

·      Ability to read existing codebases, follow established patterns, and deliver incremental improvements

·      Strong analytical problem-solving skills and attention to detail

·      Good written and verbal communication

Preferred / Nice to Have

·      Familiarity with browser automation using Selenium and Python (big plus)

·      Exposure to Celery/Redis, Django REST Framework, or common data-processing libraries

·      Basic AWS familiarity (e.g., compute, storage, monitoring) — optional but good to have

·      Experience with SaaS products, multi-tenant applications, or enterprise web systems

Domain Preference

Familiarity with the insurance industry and InsurTech is preferred but not mandatory. Strong engineering fundamentals and willingness to learn the domain matter more.

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

·      Growth path with clear impact on product and customers

Are you interested in writing agentic systems that helps companies like Coca-Cola, ITC and Lenovo drive E-commerce success? Do you want to bring Autonomy to E-commerce? Then read on and apply.

Applied Scientist - Decision AI

Location: Bengaluru

Work Schedule: Hybrid (Candidate must be based in Bengaluru - 1-2 days of WFO may be required at a later date)

About Kily

Kily is an AI company bringing autonomy to digital commerce growth. We build autonomous agents that manage Advertising, Pricing and Listings for brands and sellers across commerce marketplaces.

Performance in modern commerce shifts constantly - across marketplaces, categories and cities - faster than teams can manually track, diagnose and act on. Kily's agents work continuously against real business objectives with each brands unique context, objectives and operating constraints and keeping humans in the loop where it matters.

The Role

We are looking for an Applied Scientist to build the models and decision systems behind Kily's recommendations and actions. The work is grounded in messy, real-world commerce data help build Kily's core decision intelligence layer: systems capable of understanding complex commerce data, determining why performance is changing, deciding what should be done about it, and ultimately taking actions autonomously at scale. You will work at the intersection of learning algorithms, decision making under uncertainty and agentic systems.

What You'll Do

·      Conduct deep analysis of commerce data to derive insights, and identify gaps and new opportunities

·      Develop scalable and effective machine-learning models and optimisation strategies to solve business problems across advertising, pricing and listings

·      Define and lead science initiatives from problem framing through production deployment in a high-ambiguity environment

·      Identify and build the sequential feedback loops that make decisions improve over time

·      Design evaluation frameworks to measure the quality and business impact at scale

·      Work closely with engineering, analytics and product teams to take models from experimentation into production

What We're Looking For

·      4+ years in Applied ML/AI, Data Science. Masters or PhD in a quantitative field is a plus

·      Deep proficiency in Python, SQL, statistics and data analysis

·      Hands-on experience developing, deploying and maintaining the end-to-end lifecycle of machine-learning models

·      Experience with LLMs, fine-tuning, AI agents, optimisation or sequential decision systems is a strong plus

·      Exposure to ecommerce, marketplaces, advertising or pricing data is valuable but not essential

·      Strong problem-solving and communication skills; ML research experience is a plus

WHY KILY

Kily is already working with leading brands including ITC, Unilever, Mondelez, Coca-Cola and Lenovo, and has recently raised an INR 30 crore ($3.1 mn) Seed round led by Sorin Investments, with participation from Razorpay and Wyser Capital. You'll have the opportunity to build a foundational AI system from an early stage - one designed not merely to generate insights, but to autonomously drive real-world business

outcomes.

Senior Backend Engineer

What You'll Do :

- Build and scale the core backend and infrastructure powering a customer feedback intelligence platform - owning systems from data ingestion through real-time analytics.

- Harden ML and NLP infrastructure, including pipelines, model serving, and data flows, so features remain reliable in real-world production environments at scale.

- Own critical infrastructure decisions around data models, event flows, and service boundaries, with strong correctness and data-integrity guarantees.

- Instrument systems deeply for observability, ensuring failures surface early and production behavior becomes a source of continuous learning.

- Balance speed, cost, and long-term system health, making pragmatic, cost-effective trade-offs while shipping continuously.

- Partner closely with Product, Design, and the founding team to turn ambiguous problem statements into clear, scalable infrastructure.

- Raise the engineering bar through clean code, thorough design reviews, mentorship, and platform-level improvements.

What It Takes :

- 6-8 years of software engineering experience, with a proven track record of building and shipping reliable systems in production.

- 3+ years at a single organization where you've built infrastructure from the ground up and owned complex projects end to end.

- Deep expertise in infrastructure, including data pipelines, event-driven and microservices architectures, observability, reliability, and cost optimization.

Tech Stack :

-serverless computing, SQL/NoSQL databases, Elasticsearch, or GraphQL.

Bonus :

- Experience building or operating ML/NLP infrastructure such as data pipelines, model serving, feature stores, or inference systems.

Why This Opportunity :

- High Impact : Build foundational backend and infrastructure systems at an early-stage, high-growth technology company.

- Ownership : Take end-to-end responsibility for critical features, systems, and infrastructure.

- Complex Challenges : Work across ML/NLP infrastructure, distributed systems, data pipelines, and real-time analytics.

- Growth : Deepen your technical expertise while having the opportunity to grow into a technical leadership path.

- Culture : Work in an open, collaborative, and values-driven environment with significant autonomy.

- Benefits : Competitive compensation, equity, hybrid work setup, premium healthcare, and more.

CAP-190 : Senior Data Analyst

📍Location : Bangalore / Hyderabad / Chennai / Pune / NCR

🧠Experience : 7 - 15 Years

🆔Job Code : CAP-190

🏢Work Type : Hybrid - 3 Days in a Week

📨Application Link : https://drive.google.com/drive/folders/1bApWyMvoFHvI6krgw9CPbGZHaqYU0kSZ?usp=sharing

Your Experience at a Glance

We’re hiring a Senior Data Analyst for our client (Code Name:CAP) - CAP is a global consulting firm specializing in digital transformation and technology solutions for the financial services industry. As a Data Analyst / Senior Data Analyst at CAP, you will play a pivotal role in delivering actionable insights and supporting data migration initiatives within the financial services domain. You will collaborate with cross-functional teams to define data requirements, ensure data quality, and drive strategic solutions. This senior-level position requires strong technical expertise, stakeholder management, and a proactive approach to delivering change in a dynamic environment.

About the Client (CODE: CAP )

CAP operates at the forefront of the financial services industry, providing consulting, technology, and digital transformation solutions to leading organizations worldwide. With a focus on innovation, CAP empowers clients to navigate complex regulatory landscapes, optimize operations, and drive business growth. The company fosters a collaborative and agile culture, encouraging continuous learning and excellence.

Key Responsibilitie

● Define and obtain source data required to deliver insights and use cases.

● Determine data mapping and join multiple data sets across various sources.

● Develop methods to highlight and report data inconsistencies for user review.

● Propose and assist with suitable data migration sets for stakeholders.

● Support teams in processing data migration sets and coordinating migration activities.

● Plan, track, and coordinate the data migration team and migration run-book.

● Collaborate with stakeholders to avoid negative customer and business impacts.

● Ensure robust communication and escalation mechanisms across project portfolios.

● Implement strategic solutions and avoid short-term workarounds.

● Maintain strong control and compliance standards in data handling.

Required Skills

● Minimum 7+ years of experience as a Data Analyst, preferably in financial services.

● Strong expertise in Pyspark, Python, and SQL.

● Experience with big data programs and data models in banking or financial markets.

● Ability to write SQL queries and navigate databases such as Hive, CMD, Putty, and Note++.

● Excellent analytical skills and commercial acumen.

● Strong verbal and written communication skills.

● Proven ability to manage multiple priorities and deliver within tight deadlines.

● Business analysis skills, including defining and understanding requirements.

● Familiarity with SDLC, Agile processes, and a bias towards TDD.

● Attention to detail and a proactive, problem-solving mindset.

Nice to Have

● Knowledge and experience in Data Quality & Governance.

● Working experience with Spark Scala or Java for Spark.

● Proven track record of managing small, delivery-focused data teams (for senior roles).

● Experience with market data vendors and domains such as Party/Client, Trade, Settlements, Payments, Instrument and Pricing, Market and/or Credit Risk.

Why Join CAP (Code Name)

Join CAP to work on impactful data initiatives within the financial services sector, tackling complex technical challenges and driving meaningful business outcomes. You'll collaborate with talented professionals in a dynamic, agile environment that values

innovation and continuous improvement. CAP offers opportunities for professional growth, skill development, and the chance to contribute to high-visibility projects that shape the future of financial technology.

About the Employment Model

Direct Hire (Client Payroll) : For this role, you’ll be hired directly by the client and be part of their internal team. Straatix supports the hiring process, but your employment, payroll, and benefits are all managed by the client.

Apply here-

https://drive.google.com/drive/folders/1bApWyMvoFHvI6krgw9CPbGZHaqYU0kSZ?usp=sharing

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

• 3+ years of hands-on experience
• 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.

Location – Hyderabad (Hybrid)

Work Experience – 5 to 7 years

CTC – upto 20 LPA

Roles & Responsibilities:

· We are looking for a Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines.

· Integration of data from multiple sources or vendors to provide the holistic insights from data.

· You are expected to build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms etc.

· Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues.

· Should have experience in client interaction.

· Experience in mentoring juniors and providing required guidance.

Required Technical Skills

· Extensive hands on experience in Python, Pyspark, SQL, Dataiku.

· Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.

· Working knowledge in Databricks, Redshift, ADF etc.

· Hands-on experience in cloud services like Azure, AWS- S3, Glue, Lambda, CloudWatch, Athena.

· Sound knowledge in end-to-end Data management, Data ops, quality and data governance.

· Familiar with SFDC, Waterfall/ Agile methodology.

· Strong domain knowledge in Pharma domain/ life sciences commercial data operations.

Qualifications

· Bachelor’s or master’s Engineering/ MCA or equivalent degree.

· 5-7 years of relevant industry experience as Data Engineer.

· Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.

· High motivation, good work ethic, maturity, self-organized and personal initiative.

· Ability to work collaboratively and providing the support to the team.

· Excellent written and verbal communication skills.

· Strong analytical and problem-solving skills. 

BuyBuildSell InfraTech unifies design, manpower and material into one intelligent platform. As founding engineer, you'll architect the AI systems at its core - turning a client's plain-language request into design options, specifications and material requirements people can actually build from. Not a seat on a large team executing a settled spec: the systems you ship in month one become the foundation everything else is built on.

~ WHAT YOU'LL DO

• Build the AI reasoning layer - LLM-based intent parsing, option generation, retrieval-grounded suggestions.

• Architect the deterministic engine - rules-based calculations for specs, quantities and cost, kept strictly separate from anything AI-generated.

• Own the full stack - backend, APIs, data, frontend and infrastructure, end to end, with no platform team to hand off to.

• Ground the system in reality - work with our architects and structural engineers to encode real construction rules.

• Shape the roadmap - sit close to real usage and help decide what gets built next, not just how.

~ Qualifications:

• B.Tech / B.E. in CS, AI/ML or related.

• 2–5 years shipping production software.

• Hands-on LLM integration - prompt design,

structured output, RAG fundamentals.

• Proven end-to-end ownership: backend, data,

enough frontend/deploy to ship solo.

• Can explain, unprompted, why critical logic belongs

outside an LLM call.

Preferred:

• Early or founding engineer experience at a startup.

• Exposure to construction, real estate or physical-world marketplaces.

• Computer vision or vernacular NLP exposure (future roadmap).

• Production RAG / vector search experience - not just tutorials.

Location: Pune / Gurgaon

Position: AI Engineer

work mode: WFO

  Job Description.

​

 Job responsibilities:

• Responsibility for design, implementation and deployment of Generative AI, Agentic frameworks at scale
• Strong in programming - Python a
• Previous experience of working on Computer Vision projects and VLM /VLAM models.
• In depth awareness of Transformer architectures and End to End Deep neural networks
• Full stack AI / ML development experience
• Design, build & maintain efficient and reliable Agentic / Generative AI code leveraging pipelines
• Hosting and deployment knowledge in GCP or AWS or Azure along with advanced engineering concepts to build user friendly UI interface for easy adoption.

    Requirements:

 ·      4 to 8 years overall years of experience (Agentic AI, Generative AI, VLM, VLAM and LLM) with significant exposure in Development, Architecture design, scaling and hosting in cloud.

    Must Have –

 ·      Architecting and solutioning experience with Python and FAST API, Agentic Ai frameworks, VLMs, VLAMs, Open source LLM’s and Code based LLM models at scale with - Langchain /      Ollama, embeddings, Memory      Management etc.,

·      Practical experience in implementing Explainable and ethical AI models  Practical experience in implementing frameworks like RAG/ CAG/ Self-reflective RAG etc.,

·      Experience in cloud hosting either AWS or Azure or GCP.

·      Experience in ML-OPS - Implement a feedback mechanism to continually improve the model over time through feedback loop and monitoring KPI’s in production.

·      Experience with Quantization and Kubernetes or docker

    Good to have

·      gRPC implementation to expose the API’s on a server for easy usage and good user interface

·      Streamlit front end creation

·      Experience with SAFe framework deliveries.

Passionate about education? Join us at CK-12 !!

CK-12 (www.ck12.org) is on the lookout for talented, creative, and dedicated people to join our mission to provide great education to students around the world. We are looking for candidates to join our office in Bangalore.

We have a strong education platform that has served over 352+ Million users, have got over 2.88+ Billion questions answered, and have more than 350 thousand customized Flexbooks. We have embarked on an exciting journey to build an AI-powered student tutor and Teacher Assistant to build the next generation of learning platforms.

About CK-12 Foundation

CK-12’s mission is to provide free access to open-source content and technology tools that empower students as well as teachers to enhance and experiment with different learning styles, resources, levels of competence, and circumstances.

To achieve this noble and ambitious vision, we at CK-12 are challenging the traditional model of education to transform it dramatically. Technology has opened up lots of opportunities to revolutionize education for the benefit of students, teachers and parents.

We have chosen to be non-profit so that we can effectively realize our mission and do the right thing! It also provides us with the ability to experiment with big and bold ideas. CK-12 is backed by Vinod Khosla, a renowned technology venture capitalist.

At CK-12, you’ll experience the benefits of working in a dynamic, entrepreneurial, innovative and non-bureaucratic environment where you will get a lot of cool things done than you ever imagined! We are a small group of passionate folks who are determined to disrupt the current form of education.

Technology is key to scale education and we deeply believe in it. Come develop great solutions on our cloud-based (AWS) and AI-first platform delivering rich and interactive content.

Does our mission, people and technologies excite you? If the answer is YES! and you are a great technologist who will challenge status-quo (no order takers please!) by innovating, please come join us! Together, we will change the world!

Check out our latest product offerings

• Introducing Flexi 2.0
• Flexi, our AI-powered Student Tutor – https://www.flexi.org/
• AI-powered Teacher Assistant – https://www.ck12.org/pages/teacher-assistant/

Location: https://goo.gl/maps/NkA2Hr8JhtE3raWr5

Backend Engineer

Basic

● Design, maintain, and monitor infrastructure for data products

● Design and develop RESTful APIs for the data infrastructure

● Design, implement and drive adoption of new analytic technologies and solutions

● Work closely with data scientists, front end engineers and peers to gather requirements and

develop solutions

● Handle and resolve issues escalated from the production operational environment.

● Troubleshoot performance, reliability, and scalability issues.

● Excellent Problem solving skills

● A Code Craftsman that follows best software development and coding practices delivering

understandable and maintainable code with thorough unit tests coverage

Requirements

● 10+ years of development experience with Java, Scala, and/or Python

● Experience with writing and executing queries on RDBMS and NoSQL databases. Working knowledge of MongoDB, MySQL. We are not looking for a DBA.

● Experience with ElasticSearch, OpenSearch, Vector Embeddings, and large-scale search systems.

● Experience designing and operating high-throughput, low-latency backend services in production environments.

● Experience with horizontal and vertical scaling strategies, load balancing, caching, rate

limiting, and performance optimization.

● Experience identifying and resolving application bottlenecks through profiling, monitoring, and performance tuning.

● Experience in virtualization technologies and deployment frameworks (familiarity with working on UNIX shell, Jenkins.)

● Bachelors or masters degree in computer science or equivalent

Desired

● Experience working with FastAPI/Pylons Web Framework.

● Familiarity with messaging and distributed processing systems such as RabbitMQ, Kafka, SQS, or Celery.

● Experience designing systems to support millions of requests, large datasets, and high-concurrency workloads.

● Adept at AI Coding assistants, leveraging them beyond prompting. Working experience in Skill and tool development and usage in AI Coding tools.

● Experience with AWS EC2, Redshift, RDS, S3

Job Title : Senior Consultant – Full Stack Developer with AI

Experience : 5+ Years

Open Positions : 1

Location : Remote

Working Hours : 11:00 AM to 08:00 PM IST

Engagement : 6 to 8 Months Contract-to-Hire (C2H), with potential conversion to client payroll

Expected Joining : By the last week of August / 1st week of September

Role Overview :

Thoughtworks is looking for a Senior Consultant – Full Stack Developer with AI experience who can design and develop scalable full-stack applications while leveraging modern AI development tools and agentic AI capabilities.

The ideal candidate should have strong hands-on experience with Python, JavaScript / React.js, AWS Bedrock Agent Core, Docker, Kubernetes, and modern AI-assisted development frameworks and tools. Experience building MCP servers / tools, AI skills, or integrations using tools such as Cursor, Claude Code, Codex, or GitHub Copilot will be highly valuable.

The candidate should be comfortable working across application development, AI integration, cloud technologies, and containerized environments.

Mandatory Skills :

Python, React.js / JavaScript, AWS Bedrock Agent Core, Docker, Kubernetes, MCP / AI Skills, Cursor / Claude Code / Codex / GitHub Copilot, Full-Stack Development.

Key Responsibilities :

• Design, develop, and maintain scalable full-stack applications using modern development practices.
• Build backend services and APIs using Python and related frameworks.
• Develop responsive and scalable frontend applications using ReactJS or other JavaScript frameworks.
• Design and implement AI-powered solutions using AWS Bedrock Agent Core.
• Build and integrate AI agents, tools, skills, and workflows into enterprise applications.
• Develop and work with MCP (Model Context Protocol) servers, tools, or integrations.
• Leverage AI-assisted development platforms and coding tools such as Cursor, Claude Code, Codex, or GitHub Copilot.
• Containerize applications and services using Docker.
• Deploy, manage, and troubleshoot containerized workloads using Kubernetes.
• Collaborate with cross-functional teams to understand business requirements and translate them into scalable technical solutions.
• Follow engineering best practices around code quality, testing, security, performance, and maintainability.
• Contribute to CI/CD and cloud deployment processes; DevOps experience will be an added advantage.
• Participate in technical discussions, architecture decisions, code reviews, and project delivery.

Mandatory Skills :

• 5+ years of relevant software development experience.
• Strong hands-on experience with Python.
• Strong experience with ReactJS or another modern JavaScript framework.
• Hands-on experience with AWS Bedrock Agent Core.
• Strong experience with Docker.
• Hands-on experience with Kubernetes.
• Experience building MCP servers / tools, AI skills, or similar AI integrations.
• Experience using AI-assisted coding/development tools such as :
• Cursor
• Claude Code
• Codex
• GitHub Copilot
• Strong understanding of full-stack application development.
• Good understanding of API development, application architecture, and cloud-based solutions.

Nice to Have :

• Experience with DevOps practices and CI/CD pipelines.
• Experience with AWS cloud services beyond Bedrock.
• Experience with infrastructure automation and deployment.
• Experience building production-grade GenAI / Agentic AI applications.
• Experience with LLM integrations, AI agents, tools, and function calling.

Project Expectations :

Candidates should be able to explain at least one recent project in detail, including :

• Problem Statement : What business / technical problem were you solving ?
• Architecture & Approach : How did you design the solution ?
• Key Contributions : What did you personally build or own ?
• AI / Agent Implementation : How did you use AWS Bedrock Agent Core, MCP, or AI development tools ?
• Technology Stack : Python, React.js / JavaScript, AWS, Docker, Kubernetes, etc.
• Challenges : What were the major technical challenges ?
• Outcomes & Metrics : What measurable impact did the solution deliver, such as performance improvement, cost reduction, automation, productivity improvement, or reduced development time ?

Interview Process :

1. Round 1 – GT Technical Interview : 60 minutes
2. Round 2 – Client Technical Interview : 60 minutes
3. Round 3 – Project Round : 60 minutes
4. Additional Client Round : May be conducted on a case-by-case basis

Key Hiring Priorities :

Highest priority : Candidates with genuine hands-on experience in AWS Bedrock Agent Core + Python + React / JavaScript + Docker + Kubernetes + MCP / AI skills and practical experience using modern AI coding/agent development tools.

Note : Candidates should demonstrate hands-on implementation experience rather than only theoretical knowledge or exposure to the above technologies.

Company Overview:

Euphoric Thought Technologies is a technology-driven firm focused on building scalable software solutions for complex enterprise challenges. Operating at the intersection of data-intensive platforms and cloud-native infrastructure, the company partners with global clients to modernize their digital ecosystems. With a culture rooted in engineering excellence and pragmatic problem-solving, Euphoric Thought Technologies empowers its teams to deploy high-impact applications that serve millions of end-users across diverse industry verticals.

Role Overview:

As a Senior Python Developer based in Bangalore, you will serve as a technical anchor for our core product development initiatives. You will work closely with cross-functional teams, including product managers, frontend engineers, and DevOps specialists, to architect robust backend services that drive our platform's performance. Your daily contributions will involve translating complex business requirements into clean, maintainable code, ensuring that our systems remain resilient and efficient as we scale to meet growing user demand.

Key Responsibilities:

- Design and implement high-performance backend services using Python to ensure seamless data processing and system reliability for our enterprise clients.

- Develop and maintain RESTful APIs that facilitate smooth integration between internal microservices and external third-party platforms.

- Optimize database queries and schema designs in SQL to improve application latency and support high-concurrency environments.

- Architect and deploy cloud-native solutions on AWS, ensuring that our infrastructure remains scalable, secure, and cost-effective.

- Implement comprehensive unit and integration testing using PyTest to maintain high code quality and minimize production defects.

- Collaborate with stakeholders to refine technical specifications and mentor junior developers to foster a culture of continuous technical improvement.

Required Skillset:

- Demonstrated expertise in building and scaling production-grade applications using Python, with a deep understanding of Django and Flask frameworks.

- Proven ability to design and document RESTful APIs that adhere to industry standards for security and performance.

- Proficient in managing and optimizing complex SQL databases to support data-heavy application requirements.

- Hands-on experience in configuring and managing AWS services to support deployment pipelines and cloud infrastructure.

- Strong commitment to test-driven development, evidenced by a track record of using PyTest to ensure system stability.

- Excellent communication skills with the ability to articulate technical concepts to non-technical stakeholders and work effectively in a collaborative, office-based environment in Bangalore.

- Possess 6 to 9 years of professional software development experience, showcasing a consistent ability to deliver high-quality code in fast-paced environments.

About Nexora Group

Nexora Group is a forward-thinking technology and innovation company focused on leveraging Artificial Intelligence, Data Science, and emerging technologies to solve real-world business challenges. We provide opportunities for aspiring professionals to gain hands-on experience, work on impactful projects, and develop industry-relevant skills in a collaborative environment.

Internship Overview

We are looking for enthusiastic and motivated Data Science with AI Interns to join our growing team. This internship is designed for students and recent graduates who are passionate about data analytics, machine learning, artificial intelligence, and data-driven decision-making.

The selected candidates will work alongside experienced professionals on real-world datasets, AI models, and business intelligence projects while gaining practical exposure to industry-standard tools and technologies.

Key Responsibilities

• Collect, clean, and preprocess structured and unstructured datasets.
• Perform exploratory data analysis (EDA) and generate actionable insights.
• Assist in developing and deploying machine learning and AI models.
• Work with Python, SQL, and data visualization tools.
• Create dashboards, reports, and data-driven presentations.
• Support predictive analytics and model evaluation activities.
• Collaborate with cross-functional teams on AI-driven projects.
• Research emerging trends in Data Science, Machine Learning, and Generative AI.
• Document project findings and maintain technical reports.

Required Skills

• Basic understanding of Data Science and Machine Learning concepts.
• Knowledge of Python and data analysis libraries (Pandas, NumPy, Matplotlib, Scikit-learn).
• Familiarity with SQL and database concepts.
• Understanding of AI, Generative AI, and Large Language Models (LLMs) is a plus.
• Strong analytical and problem-solving skills.
• Good communication and teamwork abilities.
• Eagerness to learn and adapt to new technologies.

Eligibility

• Undergraduate or postgraduate students pursuing Computer Science, Data Science, AI, IT, Statistics, Mathematics, or related fields.
• Recent graduates looking to gain practical industry experience.
• Candidates with personal projects, certifications, or relevant coursework will be preferred.

What You'll Gain

• Hands-on experience with real-world AI and Data Science projects.
• Mentorship from industry professionals.
• Exposure to modern AI tools and technologies.
• Internship Certificate upon successful completion.
• Letter of Recommendation (based on performance).
• Opportunity for a Pre-Placement Offer (PPO) for outstanding performers.
• Professional networking and career development opportunities.

Understand client business requirements and translate them into technical solutions.

Conduct requirement gathering, analysis, solution design, and technical documentation.

Work closely with development, QA, infrastructure, and business teams throughout the project lifecycle.

Provide technical guidance and recommend suitable technologies, architectures, and solutions.

Participate in system integration, implementation, testing, deployment, and troubleshooting.

Analyze existing systems and identify opportunities for optimization and improvement.

Prepare technical specifications, solution documents, architecture diagrams, and project documentation.

Act as a technical point of contact for clients and internal stakeholders.

Identify technical risks, dependencies, and challenges and provide appropriate solutions.

Support pre-sales activities, including technical discussions, solution presentations, and proposal preparation when required.

Stay updated with emerging technologies, industry trends, and best practices.

Strong Software Engineer fullstack profile using NodeJS, Python, and React

2

Mandatory (Experience) - Must have 6+ YOE in Software Development using Python and NodeJS (For backend) & React (For frontend)

3

Mandatory (Core Skills 1): Must have strong experience in working on Typescript

4

Mandatory (Core Skills 2): Must have experience in message based systems like Kafka, RabbitMq, Redis

5

Mandatory (Core Skills 3): Databases - PostgreSQL & NoSQL databases like MongoDB

6

Mandatory (Company) - Product Companies Only

7

Mandatory (Education) - B.Tech or Dual degree (Btech and Mtech or Integrated Msc/MS) from Tier 1 Engineering Institutes (IITs, not NITs). Candidates from other institutions will not be considered unless they come from top-tier product companies

8

Mandatory (Note) : This role is a hybrid role (2 days WFO)

9

Preferred (Experience): Experience in Fin-Tech, Payment, POS and Retail products is highly preferred

10

Preferred (Mentoring): Experience in mentoring, coaching the team.

Founding Engineer (Full Stack Engineer)

Location: Remote (India)

About the Role

We're hiring a Mid-Senior Full Stack Engineer to build AI-powered software products from the ground up. You'll own features end-to-end across the frontend and backend, working on scalable systems, real-time applications, and AI-driven workflows.

If you enjoy solving complex engineering challenges, building production-grade applications, and working with modern technologies, we'd love to hear from you.

What You'll Do

• Build and ship end-to-end features across frontend and backend.
• Design scalable APIs, services, and database schemas.
• Develop and maintain real-time applications using WebSockets and event-driven architectures.
• Build asynchronous processing pipelines and background jobs.
• Integrate AI/LLM capabilities into production applications.
• Optimize application performance, scalability, and reliability.
• Collaborate on architecture, code reviews, and engineering best practices.
• Mentor junior engineers and contribute to technical decision-making.

Tech Stack

Frontend

• React
• Next.js
• TypeScript
• Tailwind CSS

Backend

• Python
• FastAPI
• PostgreSQL
• Redis

AI & Infrastructure

• LLM Integrations
• REST APIs
• WebSockets
• Background Workers
• Docker
• CI/CD

What We're Looking For

• Strong experience building production-grade web applications.
• Expertise in React, Next.js, and TypeScript.
• Solid backend development experience with Python (FastAPI preferred).
• Strong knowledge of PostgreSQL and Redis.
• Experience designing scalable APIs and backend services.
• Familiarity with real-time systems and asynchronous processing.
• Experience working with AI/LLM-powered applications is a strong plus.
• Strong understanding of software architecture, testing, and clean code practices.
• Ability to work independently in a remote-first environment.

Nice to Have

• Experience with LangChain, LangGraph, or similar AI frameworks.
• Experience with RabbitMQ or Celery.
• Knowledge of cloud infrastructure and DevOps.
• Experience building high-scale distributed systems.

Why Join?

• Build cutting-edge AI-native products.
• Remote-first work environment.
• High ownership and technical autonomy.
• Opportunity to influence architecture and product direction.
• Work with a highly skilled engineering team.

If you're passionate about building modern AI-powered applications and enjoy solving challenging engineering problems, we'd love to connect.

Essential Duties and Responsibilities:

• Build new automations in Python: API integrations, data pipelines, scheduled jobs, and process replacements scoped with operating partners.

• Maintain the existing Power Automate estate, both unattended cloud and desktop flows. Triage failures, repair flows, and keep unattended runs healthy on the bot-server farm. Operate the Power Platform space around them: environments, solutions, connection references, and pipeline-managed deployments.

• Migrate Power Automate flows to Python where the economics favor it. Retire flows rather than patching them indefinitely.

• Integrate systems over REST APIs. Handle JSON and XML transformation, authentication (OAuth, service principals), and error handling that survives flaky endpoints.

• Author SQL queries, tables, and stored procedures that support automations.

• Operate what you build. Instrument jobs with logging, monitoring, and alerting so failures surface before the business notices them. Write runbooks.

• Improve how automations run. Today they run as scheduled jobs on VMs. Help evaluate and move toward containerized or Azure-native execution (Functions, Container Apps) where it reduces operational load.

• Use AI coding tools as a core part of daily development, within company governance and review standards.

• Document what you build so the next engineer, or an operating partner, can understand and extend it.

Knowledge, Skills and Abilities:

• Python proficiency: clean scripting, packaging, error handling, structured logging, and enough testing to trust a job running unattended at 2 a.m.

• Power Automate strength across cloud and desktop flows: able to read, debug, and repair complex unattended flows built by someone else, plus the platform administration around them. You do not need to love the platform. You do need to support it capably, including solo coverage when other developers are out.

• REST API integration experience, including authentication patterns and rate-limit handling.

• SQL Server competence: comfortable writing T-SQL and authoring queries, tables, and stored procedures through a reviewed, versioned release process.

• Working knowledge of Azure: DevOps pipelines at minimum; Functions, Container Apps, or AKS exposure a plus.

• Daily fluency with AI-assisted development. You should be able to describe, in concrete detail, how you structure work with an agentic coding tool: what you delegate, what you review, where it fails, and how you catch it.

• PowerShell and shell scripting for glue work on Windows and Linux hosts.

• Production instincts: idempotent jobs, retries with backoff, alerting thresholds that page on real problems and stay quiet otherwise.

• Plain written and verbal communication. You will work directly with non-technical process owners who need to understand what an automation does and what to do when it stops.

Training and Experience:

• 3 to 5 years in automation engineering, RPA, or software engineering roles with automations shipped to production and operated afterward.

• A track record you can walk through: what you built, what broke, and what you changed.

• Demonstrated, current use of AI coding tools in real work. Candidates will be asked to describe their workflow in specifics; vague answers end the conversation.

Job Description:

Position: Lead / Senior Data Engineer

Location: Chennai

Shift: US Eastern Time ( 5:00 PM – 2:00 AM )

Experience : 8+ years

Notice Period: Immediate Joiner only

Roles and Responsibilities:

Role Overview

The Lead Data Engineer will be responsible for designing, developing, and delivering high-quality software and data solutions while leading a team of engineers. The role involves hands-on technical work, architectural decision-making, mentoring junior developers, and collaborating with cross-functional teams to ensure successful delivery of scalable data platforms and analytical solutions.

Key Responsibilities:

Lead the end-to-end design, development, and delivery of software systems, data pipelines, and components.

Define technical strategy, architecture, and best practices for development and data engineering.

Design and build optimized data pipelines using cutting-edge technologies in a cloud environment.

Construct infrastructure for efficient ETL processes from various sources and storage systems.

Architect, design, and maintain database pipeline architectures, ensuring readiness for AI/ML transformations.

Lead the implementation of algorithms and prototypes to transform raw data into useful information.

Review code for quality, scalability, and performance.

Collaborate with Product Managers, Business Managers, Designers, and QA teams to translate business requirements into technical solutions.

Develop analytical tools, programs, and reporting mechanisms.

Create data validation methods and data analysis tools.

Interpret data trends and patterns to establish operational alerts.

Conduct complex data analysis and present results effectively.

Prepare data for prescriptive and predictive modeling.

Ensure compliance with data governance and security policies.

Troubleshoot, debug, and resolve complex technical issues.

Drive continuous improvement in software and data development processes, tools, and methodologies.

Mentor and guide engineers through code reviews, technical discussions, and training.

Ensure timely delivery of projects while maintaining high engineering standards.

Continuously explore opportunities to enhance data quality and reliability.

Apply strong programming and problem-solving skills to develop scalable solutions.

Demonstrate passion for testing strategy, problem-solving, and continuous learning.

Willingness to acquire new skills and knowledge.

Possess a product/engineering mindset to drive impactful data solutions.

Experience working in distributed environments with global teams.

Stay current with emerging technologies and industry trends to propose innovative solutions.

Technical Skills and Experience Requirements

Minimum 8+ years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines.

High proficiency in Python, Scala, and Spark for applied large-scale data processing.

Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive.

Solid understanding of batch and streaming data processing techniques.

Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.

Expert-level ability to write complex, optimized SQL queries across extensive data volumes.

Experience with RDBMS and OLAP databases such as MySQL and Snowflake.

Familiarity with Agile methodologies.

Obsession for service observability, instrumentation, monitoring, and alerting.

Knowledge or experience in architectural best practices for building data lakes.

Qualifications - Bachelor’s degree in computer science, Engineering, Information Systems, or related field.

Job Title

Python Full Stack Developer – AI

Experience: 6-9 Years

Location: Bangalore (Hybrid)

Employment Type: Full-Time

Job Summary

We are seeking a highly skilled Python Full Stack Developer with AI expertise to design, develop, and deploy scalable AI-powered applications. The ideal candidate should have strong experience in Python, Full Stack Development, REST APIs, modern frontend frameworks, and Generative AI technologies, including LLMs, prompt engineering, and AI integrations.

The role involves building end-to-end web applications, integrating AI models, and collaborating with cross-functional teams to deliver innovative AI-driven solutions.

Key Responsibilities

· Design, develop, and maintain scalable full-stack applications using Python.

· Build responsive and interactive user interfaces using React.js, Angular, or Vue.js.

· Develop backend services and RESTful APIs using Django, Flask, or FastAPI.

· Integrate Generative AI models such as OpenAI GPT, Claude, Gemini, or Llama into business applications.

· Develop AI-powered chatbots, assistants, document processing, and workflow automation solutions.

· Implement prompt engineering techniques to optimize AI model performance.

· Build Retrieval-Augmented Generation (RAG) pipelines using vector databases.

· Work with LangChain, LangGraph, or LlamaIndex for LLM orchestration.

· Integrate AI APIs and third-party services into enterprise applications.

· Design and optimize SQL and NoSQL databases.

· Deploy applications on AWS, Azure, or GCP.

· Develop CI/CD pipelines and manage deployments using Docker and Kubernetes.

· Write clean, reusable, and well-documented code following best practices.

· Participate in Agile ceremonies, code reviews, and sprint planning.

Required Technical Skills

Backend

· Python

· Django

· Flask

· FastAPI

Frontend

· React.js / Angular / Vue.js

· HTML5

· CSS3

· JavaScript (ES6+)

· TypeScript

AI / Generative AI

· OpenAI API

· Azure OpenAI

· Gemini API

· Claude API

· Llama Models

· LangChain

Databases

· PostgreSQL

· MySQL

· MongoDB

· Redis

Cloud & DevOps

· AWS / Azure / Google Cloud Platform

· Docker

· Kubernetes

· Git

· GitHub

· Jenkins

· CI/CD

API Development

· REST APIs

· GraphQL (Preferred)

· API Integration

Preferred Skills

· Machine Learning fundamentals

· NLP (Natural Language Processing)

· Hugging Face Transformers

· TensorFlow or PyTorch

· Kafka or RabbitMQ

· Elasticsearch

· Microservices Architecture

· Authentication (OAuth2, JWT)

Qualifications

· Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

· 6–9 years of experience in Python Full Stack Development.

· Hands-on experience with Generative AI and LLM-based application development.

· Experience working in Agile/Scrum environments. 

Technical Lead – Embedded Software Application Projects

link: https://www.ziliconcloud.com/careers

ZILICONCLOUD PRIVATE LIMITED is looking for an experienced Technical Lead with 5–8 years of industry experience in Embedded Systems, IoT, AI, Cloud, and Software Engineering.

The candidate will lead Embedded, IoT, Edge AI, and Cloud projects, define system architecture, convert requirements into technical tasks, and ensure successful project execution and delivery.

Key Responsibilities

• Design modular system architectures for Embedded, IoT, Edge AI, Cloud, REST APIs, and dashboards.
• Convert requirements into clear tasks, milestones, and deliverables.
• Track project progress, manage technical risks, and ensure on-time delivery.
• Guide engineers on coding standards, Git, testing, debugging, and documentation.
• Troubleshoot issues across hardware, firmware, IoT, cloud, backend, and UI.
• Support system integration, testing, debugging, and performance improvement.
• Review technical designs, code, and test results.
• Lead prototype development, integration, technical reviews, and demonstrations.
• Mentor young engineers and explain complex technical concepts in a simple and practical way.
• 
  

Required Skills

C/C++, Python, JavaScript/TypeScript, Linux, FreeRTOS, Microcontrollers, REST APIs, MQTT, Git, Embedded Software, IoT, and system debugging.

Preferred: AWS IoT, Microsoft Azure, ThingsBoard, OpenCV, TensorFlow Lite (TFLite), React, Flutter, or FastAPI.

Education

B.E./B.Tech/M.E./M.Tech in ECE, CSE, Embedded Systems, Mechatronics, or a related field.

📍 Location: East Tambaram, Chennai, Tamil Nadu

💼 Experience: 5–8 Years

🕒 Employment Type: Full-Time

About the Role

We are looking for a Senior Data Engineer with strong hands-on expertise in Databricks, Python, PySpark, and SQL to build scalable, high-performance data engineering solutions. You’ll architect and develop large scale, high-performance data pipelines capable of handling massive real-time and batch data volumes across multiple business systems. Databricks is the core enterprise data and processing platform for this role. You will also use Apache Airflow for workflow orchestration and dbt for ELT transformations, and will contribute to designing reliable, secure, and governed data platforms that enable analytics, reporting, and AI-driven use cases.

Key Responsibilities

• Design and implement large-scale data pipelines using Python/PySpark, Databricks, and Microsoft Fabric.
• Develop and optimize data processing workloads in Databricks using PySpark and Spark SQL, with a strong focus on scalability, reliability, performance, and maintainability.
• Develop and maintain dbt models including layered architecture, incremental models, snapshots, macros, testing, and documentation.
• Design, develop, and maintain Apache Airflow DAGs for orchestrating reliable, scalable, and observable data pipelines.
• Design and implement data quality, observability, and governance frameworks, including automated testing, monitoring, lineage, access control, and data privacy standards.
• Partner with analytics, product, and business stakeholders to turn requirements into trustworthy datasets, and raise the engineering bar through design discussions, code reviews, and mentoring junior engineers.

Required Skills

• Strong expertise in Python for developing scalable, modular, and production-ready data engineering applications.
• Strong expertise in PySpark, including DataFrame API, Spark SQL, Structured Streaming, partitioning strategies, joins, caching, handling data skew, and Spark performance optimization.
• Strong hands-on experience with Databricks for data ingestion, transformation, processing, and optimization, including Delta Lake, Unity Catalog, Databricks Workflows, notebooks, jobs, and Databricks-native data engineering capabilities.
• Strong experience in Databricks/Spark performance tuning, including query and job optimization, partitioning, file sizing, caching, join optimization, handling data skew, and efficient use of compute resources.
• Hands-on experience with Delta Lake, including transactional data processing, schema management, incremental data processing, and reliable batch and streaming data pipelines.
• Hands-on experience in developing dbt projects using layered architecture, incremental models, snapshots, macros/Jinja, testing, documentation, and deployment best practices.
• Expertise in advanced SQL and data modelling — dimensional modeling, slowly changing dimensions, schema evolution, and query optimization.
• Hands-on experience in developing and managing Apache Airflow DAGs, scheduling workflows, dependency management, retries, backfills, and operational monitoring.
• Hands-on experience with at least one major cloud platform (AWS, Azure or GCP).
• Strong problem-solving skills and the ability to work independently with business and analytics stakeholders.

Nice to Have

• Hands-on exposure to Microsoft Fabric for data integration and analytics.
• Experience using AI coding assistants (e.g. Claude Code, GitHub Copilot) as part of a development workflow.
• Familiarity with modern DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and containerization (Docker/Kubernetes).
• Domain expertise in financial services.

Role Summary

We are looking for an accomplished PowerBi Solution architect to architect and drive scalable, insight-rich analytics solutions across the enterprise. This role sits at the intersection of data engineering, business intelligence, and solution architecture—ideal for a candidate with mastery of modern visualization tools, modeling strategies, and end-to-end data integration.

Key Responsibilities

● Architect and implement scalable Power BI solutions that span data modeling, integration, visualization, and performance tuning

● Design and lead the development of enterprise-grade data models using Star, Snowflake, and composite architecture

● Lead the integration of cloud-based data warehouse platforms including Oracle ADW and Snowflake

● Lead the development of scalable, interactive dashboards using Power BI, driving self-service analytics across business units

● Develop ETL and ELT pipelines to ingest and transform structured, semi-structured, and API-driven data sources

● Implement automated data ingestion and transformation using Python and shell scripting for performance and reliability

● Handle and harmonize data from diverse API sources across applications, platforms, and third-party services

● Deliver interactive dashboards and storytelling experiences tailored for executives, analysts, and operational teams

● Optimize semantic layers, DAX calculations, and deployment pipelines for reusability and governance

● Mentor BI developers and analysts, setting architectural standards and fostering collaboration across analytics teams

● Collaborate with cross-functional teams to translate strategic business goals into robust analytics solutions

Required Qualifications

● 8+ years in Power BI development and analytics Engineering, with 3+ years in architecture leadership roles

● Strong command of DAX, M Query, and performance tuning best practices

● Deep experience in data modeling (Star, Snowflake, composite) and cross-platform architecture

● Hands-on expertise in Oracle ADW, Snowflake, and API-based data ingestion

● Proficiency in Python, shell scripting, and automation of analytics pipelines

● Strong background in ETL/ELT development, data quality assurance, and deployment orchestration

● Demonstrated success in solution architecture across cloud ecosystems such as Azure, Oracle OCI

Preferred Skills

● Experience with Power BI Premium capacity management and deployment pipelines

● Experience with DAX, M language, and performance tuning technique

● Experience integrating third-party BI tools, data lakehouses, and stream processing services

● Effective communicator capable of translating technical architecture into business value

● Exposure to MS Fabric and Azure Data Factor

Strong AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

3

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

4

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

5

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

6

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

7

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

8

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

9

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

10

Mandatory (Age) - Candidate's Age should be below 28 Years

11

Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.

12

Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..

13

Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.

14

Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies

15

Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

Software Development Engineer

What you'll do

Be the dedicated engineer for one of our clients. Learn their business, find what to automate, and build it.

Build automations, integrations, and web apps on whatever the client runs business platforms like the Zoho suite, cloud services like Azure, and custom apps where needed.

Work with APIs every day: connect systems, move data, make tools talk to each other.

Own work end to end: hear the problem from the stakeholder, build the solution, ship it, demo it, support it.

Resolve client tickets and bugs fast. Keep their systems and data healthy.

Write things down: clear docs, clear updates, clear commit history.

What we're looking for

2–5 years shipping software that works and being able to read it, debug it, and stand behind it.

Strong with REST APIs and integrations between systems.

Happy working inside business platforms (Zoho, Salesforce, or similar). Much of the leverage in this role lives there, not in custom code.

You can sit in a call with a non-technical client, understand the real problem, and come back with a working solution.

Self-driven. You'll often be the only engineer on a problem.

Why you'll love this role

Full ownership from first call to delivery you run projects, not just a ticket queue.

Direct access to clients and leadership. Your decisions ship the same week.

Constant variety: new systems, new problems, new builds.

As a Senior Machine Learning Engineer at Quantiphi, you will be responsible for designing and developing advanced machine learning models and algorithms to solve complex business problems. You will work on optimizing and deploying these models on AWS infrastructure, ensuring scalability and reliability.

Must have skills:

● Experience with LangChain, LangGraph, LlamaIndex, CrewAI, or similar Agentic AI frameworks.

● Python: Good exposure to Python (Pandas, NumPy, FastAPI, advanced Python concepts).

● AWS Bedrock: Hands-on experience with AWS Bedrock and foundation models such as Claude Haiku and Claude Sonnet.

● LLM & GenAI: Hands-on experience in developing RAG pipelines, Prompt Engineering, and LLM-based GenAI applications.

● ML Pipeline Architecture: Experience with Titan Embeddings, Amazon OpenSearch Vector Search, and vector-based retrieval.

● Agentic AI: Hands-on experience with Agentic AI frameworks and AWS Bedrock AgentCore for developing AI agents and workflow orchestration.

● AI Agents & Knowledge Base: Experience developing AI agents for customer query automation and Knowledge Base (KB) solutions.

● Experience with document parsing, chunking, vectorizing and re-ranking strategies.

● Guardrails & Security: Experience configuring AWS Bedrock Guardrails and implementing authentication and authorization for secure AI applications.

● AWS Services: Hands-on experience with API Gateway, Lambda, S3, IAM, CloudWatch, ECR, and SageMaker.

● Software Engineering: Experience with Git, REST APIs, and CI/CD pipelines.

● Relevant AWS certifications (e.g., AWS Certified AI Practitioner, AWS Certified Machine Learning Engineer – Associate, or AWS Certified Solutions Architect – Associate) are a plus.

Good to have skills:

● Hands-on experience with OCR/Document Intelligence engines and NLP techniques for extracting structured information from documents and images.

● Hands-on experience with Bedrock Agentcore

● Hands-on experience with OpenAI, Anthropic, Gemini, or other foundation models.

● Experience with Docker, Kubernetes, and MLOps practices.

● Experience with Redshift, SQL, DynamoDB, or AWS Glue.

● Exposure to model monitoring, evaluation, and observability for GenAI applications.

● Ability to work in an Agile and DevOps environment.

Location - Remote (India)

Key Responsibilities 

• Design, develop, and maintain database schemas, stored procedures, views, and queries in SQL Server and MySQL. 

• Identify and resolve query performance bottlenecks using execution plans, indexing strategies, and tuning techniques. 

• Conduct regular database health checks and performance reviews to ensure optimal operation. 

• Collaborate with development and operations teams to support application data requirements. 

• Write and optimize complex SQL scripts to meet business and operational needs. 

• Support the DBA Team Lead with day-to-day database operations and incident resolution. 

• Assist in monitoring database availability, integrity, and backups. 

• Document database structures, procedures, and changes in a clear and organized manner. 

• Implement best practices for data storage, retrieval, and processing efficiency. 

• Contribute to the continuous improvement of database standards and internal processes. 

• Identify and effectively prioritize situations requiring urgent attention. 

• Stay current with system information, database technologies, changes, and updates. 

• Experience with cloud-managed databases (e.g., Microsoft Azure SQL Database, Amazon RDS) and understanding of scaling, cost optimization, and high availability in cloud environments. 

• Hands-on exposure to database automation and CI/CD practices (schema versioning, deployment pipelines, Infrastructure as Code). 

• Strong knowledge of high availability and disaster recovery design, including replication, failover, and defined RPO/RTO ownership. 

• Familiarity with database security best practices (encryption, access control, auditing, and protection of sensitive/regulated data). 

• Experience with monitoring and observability tools, with a proactive approach to performance tuning and alerting. 

• Scripting ability (PowerShell, Python, or Bash) to automate routine database operations and reduce manual effort. 

• Experience with database migrations, version upgrades, or modernization initiatives (on-prem to cloud or legacy to current platforms). 

• Ability to operate in a DevOps-oriented environment, partnering closely with engineering teams and owning database performance tied to application SLA. 

• Proficiency in T-SQL and/or standard SQL. 

• Ability to multi-task and adjust priorities quickly in a fast-paced environment. 

• Ability to research and implement solutions using available technical resources. 

• Strong analytical and problem-solving skills with attention to detail. 

• Ability to clearly communicate technical concepts to non-technical stakeholders. 

• Advanced knowledge of database performance tuning and query optimization. 

• Familiarity with cloud database platforms such as Microsoft Azure SQL, AWS   RDS, or equivalent. 

• Experience with database deployment automation and CI/CD pipelines. 

• Understanding of high availability, disaster recovery, and data protection strategies. 

• Working knowledge of database monitoring and performance management tools. 

• Basic scripting skills (PowerShell, Python, or Bash) for automation. 

• Awareness of data security and compliance considerations in regulated environments. 

Required Skills 

• Proven working experience as a Database Administrator or in a similar role. 

• Working knowledge of Microsoft SQL Server (SSIS, T-SQL, DDL, SML) 

• Working knowledge of MySQL or MariaDB. 

• A minimum of 5 years of experience in database administration. 

• Understanding of database normalization and data modeling principles. 

Nice to Have 

• MacOS, iOS, Android, Linux OS beneficial but not required. 

• ETL processes or data warehouse experience beneficial but not required. 

• Microsoft Certified: Azure Database Administrator Associate or equivalent SQL Server certification preferred but not required. 

• MySQL certification preferred but not required. 

Strong Software Engineer fullstack profile using NodeJS, Python, and React

2

Mandatory (Experience) - Must have 6+ YOE in Software Development using Python and NodeJS (For backend) & React (For frontend)

3

Mandatory (Core Skills 1): Must have strong experience in working on Typescript

4

Mandatory (Core Skills 2): Must have experience in message based systems like Kafka, RabbitMq, Redis

5

Mandatory (Core Skills 3): Databases - PostgreSQL & NoSQL databases like MongoDB

6

Mandatory (Company) - Product Companies Only

7

Mandatory (Education) - B.Tech or Dual degree (Btech and Mtech or Integrated Msc/MS) from Tier 1 Engineering Institutes (IITs, not NITs). Candidates from other institutions will not be considered unless they come from top-tier product companies

8

Mandatory (Note) : This role is a hybrid role (2 days WFO)

9

Preferred (Experience): Experience in Fin-Tech, Payment, POS and Retail products is highly preferred

10

Preferred (Mentoring): Experience in mentoring, coaching the team.

Senior Xano Developer

Visual Backend Development, APIs & AI-Assisted Build

📍 Mumbai (On-site) | Full-time | 3-5 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Xano Developer who will build backend systems and APIs for our customer engagements on Xano, the visual backend development platform.

The mandatory requirement for this role is hands-on production backend engineering experience, including PostgreSQL data modelling and REST API design, in either a Node.js or Python environment.

Prior production work on Xano is strongly preferred.

The role is hands-on and customer-facing. You will own backend delivery across engagements: designing data models, building API flows in Xano, integrating third-party services, and partnering with frontend, mobile, and AI engineers on contracts and behaviour.

The work spans all three Xano build modes: no-code function stacks, custom code through Xano’s scripting and code blocks, and Xano’s AI assistance and agentic features.

A typical week includes a data model review for a new engagement, building a complex API flow in Xano, integrating a third-party webhook, and a customer working session on a new module.

Responsibilities:

Backend Delivery on Xano

Own end-to-end backend implementation on Xano: database schema, API endpoints, function stacks, background tasks, and integrations.

Ship production-ready work that meets customer requirements and engineering quality standards.

Build Across All Three Xano Modes

Use Xano’s no-code function stacks for standard CRUD and business logic.

Drop into custom code (JavaScript, Python through code blocks, expressions) where visual flows would be unwieldy.

Use Xano’s AI assistance and agentic features to accelerate routine build work.

Database Design on PostgreSQL

Own data model decisions for each engagement: table design, relationships, indexes, addons, and query performance.

Make schema choices that hold up as product usage grows and that map cleanly to the API contracts the client needs.

API Design and Integration

Design clean REST API contracts that the frontend, mobile, and third-party consumers can rely on.

Cover authentication, input validation, pagination, error handling, and rate limiting.

Integrate external services (payment gateways, messaging, storage, AI providers) through Xano’s connectors and custom requests.

Product Thinking and Solutioning

Translate fuzzy product asks from customers into concrete backend solutions.

Ask the right questions about edge cases, data lifecycle, multi-tenancy, and access control before building.

Push back on requirements that will cause pain later.

Customer Communication

Work directly with customers in discovery, design reviews, demos, and weekly working sessions.

Explain trade-offs in plain language, present options with clear recommendations, and write tight technical updates.

AI-Assisted Backend Development

Use Xano’s built-in AI features as well as external AI tools (Claude, Cursor, and similar) day to day for schema drafts, function stack scaffolding, query writing, integration setup, and review.

Develop strong instincts for when AI output is usable as-is and when it must be reworked.

Quality, Testing, and Reliability

Test the flows you ship.

Set up sensible error handling, logging, and alerts for the backend services you own.

Participate in incident response when something breaks in production.

Documentation and Handover

Document data models, API contracts, and non-obvious decisions inside Xano and in shared docs so the rest of the team and the customer can pick up the work without you in the room.

Continuous Learning

Track changes to the Xano platform, including new features, performance improvements, and AI capabilities.

Apply them to active engagements where they reduce build effort or improve product outcomes.

Requirements:

Hands-on Production Backend Engineering Experience (Mandatory)

Must have personally shipped backend systems to production for real users, with ownership of API design and data modelling.

POCs, coursework, and internal-only tools do not qualify.

3 to 5 Years of Professional Backend Engineering Experience

In either a Node.js or Python environment.

Candidates with slightly less time but strong demonstrated ownership are welcome to apply.

Strong PostgreSQL Skills

Schema design, indexing, query writing, and migrations on at least one production system.

Able to reason about query performance and design data models that hold up under realistic product usage.

REST API Design and Integration Depth

Comfort designing API contracts that are clean, predictable, and easy for frontend, mobile, and third-party consumers to work with.

Experience integrating external services such as payment gateways, messaging providers, storage, and AI APIs.

Familiarity with at Least One Node.js or Python Backend Stack

Such as Express, NestJS, Fastify, FastAPI, Django, or Flask.

Comfort reading and writing application code outside of visual environments when the situation calls for it.

Product Thinking and Solutioning

Ability to take a fuzzy product brief, ask the right questions, and propose a backend design that is fit for purpose.

Strong instincts for what to build first, what to defer, and what not to build.

Strong Written and Spoken English Communication

Confident in customer working sessions and design reviews.

Comfortable writing precise technical documentation and explaining trade-offs to non-engineering stakeholders.

Cloud and Deployment Fundamentals

Working knowledge of at least one of AWS, GCP, or Azure: deploying services, reading logs, managing environments, and basic operational tasks.

Familiarity with Docker is a plus.

Bachelor’s Degree

Bachelor’s degree in Computer Science, Information Technology, or a related engineering discipline.

Exceptional candidates with demonstrable production experience and strong portfolios may be considered without a formal degree.

Nice to Have

• Prior production experience on Xano, Bubble, Retool, or comparable visual or low-code backend platforms
• Full stack experience with React, Next.js, React Native, or Flutter
• Experience integrating LLM APIs (OpenAI, Anthropic, Google) into backend workflows
• Multi-tenant SaaS product experience
• Prior agency, consulting, or product-engineering experience

Software Developer

We are looking for a skilled Developer to design, develop, test, and maintain web and mobile applications. The candidate should have experience with modern development technologies, APIs, databases, cloud platforms, Git/GitHub, and AI integration. Good problem-solving, teamwork, and communication skills are required.modern full-stack developer, a strong combination is React/Next.js + Node.js/Python + PostgreSQL/MongoDB + Git/GitHub + AWS + AI/API integration.

Forward Deployed Engineer (FDE) – KnackLabs.ai

As a Forward Deployed Engineer at knacklabs.ai, you will sit at the intersection of engineering and customer success. You'll embed directly with customer teams to understand their workflows, rapidly prototype and ship solutions using our platform, and turn those learnings into product improvements. This role is ideal for engineers who want high ownership, fast feedback loops, and direct exposure to how their code changes a customer's business.

What you will own

1. Customer embedding
2. Work directly with customers to understand their business processes, pain points, technical environments, and existing ERP/application landscape.
3. Solution building
4. Design, build, and deploy custom integrations, workflows, and applications on top of the knacklabs.ai platform.
5. Product feedback loop
6. Turn one-off customer builds into reusable, generalizable features by working closely with the core product and engineering teams.
7. Rapid prototyping
8. Write production-quality code under real deadlines, balancing speed with maintainability.
9. Technical troubleshooting
10. Debug issues across the stack, from data pipelines to APIs to front-end integrations, in live customer environments.
11. Ongoing ownership
12. Own the technical relationship with select customers post-deployment, ensuring solutions remain stable and scale with their needs.
13. Travel
14. Travel to customer sites as needed, expected occasionally and varying by account.

What we need from you

1. Three or more years of professional software engineering experience, ideally including customer-facing or implementation work.
2. Strong proficiency in at least one backend language (Python, Node.js, Go, or similar) and comfort working across a full stack.
3. Experience with REST/GraphQL APIs, databases (SQL/NoSQL), and cloud platforms (AWS, GCP, or Azure).
4. Proven experience building and deploying AI-driven solutions within enterprise application ecosystems, including ERP integrations, workflow automation pipelines, and end-to-end product development, with a track record of hands-on stakeholder engagement across technical and business teams.
5. Hands-on experience with ERP systems such as ERPNext/Frappe, SAP, Oracle ERP, Microsoft Dynamics/Navision/Business Central, Odoo, or similar enterprise ERP platforms, including experience with ERP implementation, customization, workflow/module modifications, integrations, or building applications on top of ERP systems, is strongly preferred.
6. Demonstrated ability to work independently in ambiguous, fast-changing environments.
7. Strong communication skills. You can explain technical tradeoffs clearly to both engineers and non-technical stakeholders.
8. A bias toward action. You are comfortable shipping a working solution today rather than a perfect one next month.

About the Role

We are looking for a Forward Deployed Engineer with strong hands-on experience in Databricks and AI-assisted software development using Cursor. The role is suited for an engineer who can work directly with clients and internal teams to understand business problems, rapidly build solutions, and take them from prototype to production.

The ideal candidate should have strong expertise in Python, SQL, Databricks, PySpark, data engineering, APIs, and modern AI-assisted development workflows, along with excellent problem-solving and client-facing skills.

Key Responsibilities

Forward Deployed Engineering

• Work directly with clients and stakeholders to understand business and technical requirements.
• Translate business problems into scalable technical and data solutions.
• Rapidly prototype, test, iterate, and productionize solutions.
• Collaborate with engineering, data, AI, and delivery teams to implement customer solutions.
• Troubleshoot production issues and continuously improve deployed solutions.
• Act as a technical bridge between clients and internal engineering teams.

Databricks & Data Engineering

• Design and develop scalable data solutions using Databricks, PySpark, Python, and SQL.
• Build and optimize ETL/ELT and data processing pipelines.
• Work with Databricks Lakehouse, Delta Lake, Unity Catalog, and Databricks Workflows.
• Develop data ingestion and transformation pipelines for structured and semi-structured data.
• Optimize Databricks workloads for performance, scalability, reliability, and cost.
• Integrate Databricks with databases, APIs, cloud platforms, and enterprise applications.

Cursor & AI-Assisted Development

• Use Cursor and AI-assisted development workflows to accelerate software development, debugging, refactoring, and documentation.
• Effectively use AI coding assistants to understand existing codebases and develop new features.
• Apply appropriate engineering judgment to review, validate, test, and secure AI-generated code.
• Use AI-assisted development for rapid prototyping and proof-of-concept development.
• Work with modern AI/LLM APIs and tools where required for customer solutions.
• Stay current with emerging AI-assisted software engineering practices.

Production & Deployment

• Develop production-ready applications, APIs, and data pipelines.
• Work with Git, CI/CD, APIs, containers, and cloud environments.
• Monitor application and pipeline performance and resolve production issues.
• Ensure solutions meet requirements for scalability, security, reliability, and maintainability.
• Collaborate with Data Scientists and ML Engineers to integrate AI/ML capabilities into production systems.

Required Skills & Experience

• 4+ years of experience in Software Engineering, Data Engineering, AI Engineering, or a related field.
• Strong hands-on experience with Databricks.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Delta Lake and Lakehouse architecture.
• Experience building production-grade data pipelines.
• Hands-on experience with Cursor or similar AI-powered coding assistants.
• Strong understanding of REST APIs and system integrations.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Strong debugging, problem-solving, and analytical skills.
• Excellent communication and client-facing abilities.

Preferred Skills

• Experience with Databricks Unity Catalog, Workflows, and MLflow.
• Experience with Generative AI / LLM applications.
• Knowledge of Claude, OpenAI, Azure OpenAI, or other LLM platforms.
• Experience with RAG, vector databases, embeddings, or AI agents.
• Experience with Docker, Kubernetes, and CI/CD.
• Experience in a consulting, customer-facing engineering, or professional services environment.
• Exposure to Agile/Scrum methodologies.

Key Competencies

• Strong problem-solving and ownership mindset
• Ability to work in ambiguous and fast-paced environments.
• Strong client/stakeholder management skills.
• Ability to understand business requirements and convert them into technical solutions.
• Strong communication and presentation skills.
• Ability to rapidly learn new technologies and tools.
• Comfortable working with AI-assisted development while maintaining high engineering standards.

Education

• Bachelor's or master’s degree in computer science, Information Technology, Engineering, Data Science, or a related discipline.

Role Summary:

We are looking for a Forward Deployed Engineer with strong hands-on experience in Databricks and Generative AI/Claude to work closely with clients, business stakeholders, and internal engineering teams. The ideal candidate will combine strong Data Engineering, Software Engineering, Databricks, and Generative AI skills with the ability to understand business problems and rapidly build, deploy, and optimize production-ready solutions. This is a client-facing, hands-on engineering role where you will work from problem discovery and solution design through POC development, production deployment, and ongoing optimization.

Key Responsibilities:

Forward Deployed Engineering

• Work directly with clients and stakeholders to understand business and technical requirements.
• Translate business problems into scalable data, AI, and software solutions.
• Design and develop POCs and rapidly validate technical solutions.
• Convert successful POCs into reliable, production-ready applications.
• Work closely with client engineering and data teams during implementation and deployment.
• Troubleshoot production issues and continuously optimize deployed solutions.
• Act as a technical bridge between clients, delivery teams, data engineers, AI engineers, and architects.

Databricks & Data Engineering

• Design and develop scalable data solutions using Databricks, PySpark, Python, and SQL.
• Build and optimize data ingestion, transformation, and ETL/ELT pipelines.
• Work with Databricks Lakehouse, Delta Lake, and Unity Catalog.
• Develop Databricks Workflows and production data pipelines.
• Implement data processing solutions for structured and semi-structured datasets.
• Optimize Databricks workloads for performance, scalability, reliability, and cost.
• Integrate Databricks with databases, APIs, cloud platforms, and enterprise applications.

Generative AI & Claude

• Build enterprise AI solutions using Claude and other Large Language Models (LLMs).
• Integrate Claude APIs into applications and business workflows.
• Develop RAG (Retrieval-Augmented Generation) solutions using enterprise data.
• Work with embeddings, vector search, semantic search, and knowledge retrieval.
• Develop AI-powered applications for summarization, classification, information extraction, question answering, and document processing.
• Implement prompt engineering, structured outputs, tool/function calling, and context management.
• Develop and integrate AI agents and multi-step AI workflows where applicable.
• Evaluate LLM responses for accuracy, relevance, groundedness, latency, and cost.
• Implement appropriate AI guardrails, security, and data privacy controls.

Production & Deployment

• Deploy AI and data solutions into production environments.
• Work with APIs, microservices, Git, CI/CD, containers, and cloud platforms.
• Monitor application and pipeline performance and troubleshoot issues.
• Collaborate with Data Scientists and ML Engineers to productionize AI/ML models.
• Ensure solutions meet security, scalability, reliability, and maintainability requirements.

Required Skills & Experience

• 4+ years of experience in Data Engineering, Software Engineering, AI/ML Engineering, or a related field.
• Strong hands-on experience with Databricks.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Delta Lake and Lakehouse Architecture.
• Experience working with Generative AI / LLMs.
• Hands-on experience with Claude / Anthropic APIs is preferred.
• Experience with RAG, embeddings, vector databases, and semantic search.
• Strong understanding of REST APIs and enterprise integrations.
• Experience developing production-grade applications and data pipelines.
• Strong problem-solving and troubleshooting capabilities.
• Excellent communication and client-facing skills.

Preferred Skills

• Experience with Claude Code / Anthropic ecosystem.
• Experience with OpenAI, Azure OpenAI, AWS Bedrock, or other LLM platforms.
• Experience with LangChain, LangGraph, LlamaIndex, or equivalent frameworks.
• Experience with Databricks Unity Catalog, Workflows, and MLflow.
• Experience with AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, and CI/CD.
• Exposure to AI agents and agentic workflows.
• Knowledge of AI evaluation, guardrails, security, and responsible AI.
• Experience working in consulting, client delivery, or customer-facing engineering environments.

Key Competencies

• Strong customer-facing and stakeholder management skills.
• Ability to understand ambiguous business problems and translate them into technical solutions.
• Strong ownership and execution mindset.
• Ability to rapidly prototype, iterate, and productionize solutions.
• Strong analytical and troubleshooting skills.
• Comfortable working in fast-paced and dynamic client environments.
• Excellent written and verbal communication.
• Ability to work independently as well as collaboratively with distributed teams.

Strong hands-on experience with Adobe Workfront.

Workfront configuration and administration.

Workflows, approval processes, templates, queues, reports, and dashboards.

Custom Forms and Custom Fields.

Strong understanding of Workfront data model and project/work management processes.

Hands-on experience with Workfront Fusion.

Experience with REST APIs, webhooks, JSON, HTTP methods, and integrations.

Experience integrating Workfront with third-party enterprise applications.

Knowledge of automation and iPaaS concepts.

Good understanding of data mapping, transformations, error handling, and integration monitoring.

Knowledge of JavaScript or scripting is an advantage.

POSITION OVERVIEW

We are seeking an experienced Senior Data Scientist & Generative AI Specialist on a contractual basis to support a premier Germany-based chemical manufacturing enterprise. In this role, you will lead the end-to-end design, development, and deployment of production-grade GenAI applications, multi-modal LLM workflows, and advanced retrieval platforms tailored to complex industrial and enterprise data ecosystems.

Working closely with cross-functional global teams, you will build robust backend microservices, implement state- of-the-art RAG/GraphRAG architectures, and leverage cloud-native AI infrastructure (Azure, Vector DBs, Knowledge Graphs) to drive operational efficiency and data-driven innovation.

KEY RESPONSIBILITIES

• GenAI & LLM System Engineering: Design, build, and deploy production-grade multi-modal GenAI applications processing text, structured technical documentation, images, and telemetry data.
• Advanced RAG & Graph Architecture: Implement cutting-edge Retrieval-Augmented Generation (RAG) and GraphRAG pipelines using document parsing frameworks, custom embeddings, vector databases, and knowledge graphs to capture complex domain relationships.
• Scalable Backend Development: Architect high-throughput, low-latency microservice APIs using Python, FastAPI, and Flask, leveraging asynchronous programming (asyncio) and strict type validation (Pydantic) for long-running LLM processes.
• Agentic Systems & Azure Ecosystem: Build autonomous agent systems using modern frameworks (MCP, A2A) and orchestrate enterprise workflows across the Microsoft Azure AI ecosystem (Azure AI Foundry, AI Search, Document Intelligence, Databricks).
• Model Optimization & Evaluation: Execute systematic LLM fine-tuning, prompt optimization, and rigorous evaluation frameworks to assess AI output accuracy, reliability, and business impact against industrial requirements.
• Data Layer Management: Architect and maintain enterprise database layers combining SQL (PostgreSQL) for structured transactional data with specialized vector search engines and graph stores.
• Rapid Prototyping: Utilize AI-assisted development tools (Copilot, Claude Code) to accelerate delivery timelines and rapidly build functional UI prototypes for client feedback.

TECHNICAL QUALIFICATIONS

Core Development & Backend:

• Python Mastery: Deep expertise in writing clean, production-ready Python using asynchronous programming (asyncio), strict type-hinting (Pydantic), and automated testing patterns.

• Backend Microservices: Hands-on experience building microservices with FastAPI and Flask structured to handle asynchronous, long-running AI background tasks.

• Database Engineering: Strong command of PostgreSQL, relational schema design, vector indexing, and knowledge graph paradigms.

Machine Learning & AI Infrastructure:

• Model Expertise: Hands-on experience with leading multi-modal LLM architectures (OpenAI, Anthropic, Google) and domain-specific AI workflows.

• Retrieval & Parsing: Proven track record with document extraction frameworks, embedding models, vector search engines, and GraphRAG architectures.

• Cloud Infrastructure: Strong proficiency with Azure AI infrastructure (Foundry, Databricks, AI Search, Document Intelligence).

• Agentic Frameworks: Practical experience with open-source agent protocols (MCP, A2A), parameter-efficient fine-tuning (PEFT/LoRA), and model evaluation methodology.

CONTRACT & REMOTE REQUIREMENTS

• Contract Engagement: Contractual structure tailored to project milestones and deliverables.

• 100% Remote Setup: Fully equipped home office with high-speed, secure internet infrastructure.

• Timezone Overlap: Guaranteed 4-hour daily overlap with Central European Time (CET/CEST - Germany) to ensure smooth collaboration with enterprise stakeholders.

• Communication: Fluent professional English communication skills (written and spoken) for asynchronous and real-time technical coordination. 

About the company

The client is a quantitative investment firm focused on Indian financial markets. They operate a multi-strategy, multi-manager platform designed to generate consistent, risk- adjusted returns.

Their approach combines systematic investment methods, rigorous quantitative research and institutional-grade manager evaluation. We bring together research, technology and data to build scalable investment solutions.

Role Overview

We are seeking a Quantitative Developer with strong C++ and Python expertise to convert mathematical models and research prototypes into reliable, high-performance analytical engines.

You will work closely with Quantitative Research, Data Engineering, AI and Product Engineering teams throughout the full model lifecycle—from research handover and production implementation to validation, deployment and ongoing support.

This role is ideal for someone who enjoys working at the intersection of quantitative finance, numerical computing and production software engineering.

Key Responsibilities

Research Production

• Translate mathematical models and Python research prototypes into robust, production-quality C++.
• Develop reusable components for risk analytics, forecasting, portfolio analysis and simulation.
• Build efficient Python interfaces for C++ components using pybind11 or similar technologies.
• Ensure production implementations remain mathematically and numerically consistent with the underlying research.
• Establish clear and reproducible processes for transitioning models from research to production.

Engine Development and Validation

• Design and develop analytical engines capable of processing historical, batch and streaming data.
• Integrate calculation components with data pipelines, APIs, databases and downstream applications.
• Validate production implementations against research prototypes, benchmark datasets and expected results.
• Develop automated numerical, unit, integration, regression and performance tests.
• Identify and resolve numerical stability, precision and edge-case issues.
• Optimize calculation speed, memory usage, concurrency and scalability.
• Profile and benchmark critical components to meet defined performance requirements.

Deployment and Delivery

• Package analytical engines as libraries, services, APIs or containers.
• Support deployment across internal infrastructure and client-controlled environments.
• Configure engines for different datasets, workflows and institutional requirements.
• Assist with integration testing, production upgrades, issue diagnosis and technical troubleshooting.
• Implement appropriate logging, monitoring and error-handling capabilities.
• Document interfaces, assumptions, configurations, dependencies and deployment requirements.

Collaboration and Ownership

• Work closely with Quantitative Research, Data Engineering, AI and Product Engineering teams.
• Participate in technical design discussions, code reviews and quantitative model reviews.
• Communicate implementation trade-offs, constraints and risks clearly to technical and quantitative stakeholders.
• Take end-to-end ownership of assigned components, from research handover through production deployment and support.
• Contribute to engineering standards, reusable libraries and development best practices.

Required Qualifications

• Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, Statistics, Physics, Quantitative Finance or a related discipline.
• Strong professional programming experience in modern C++, including object- oriented and generic programming.
• Proficiency in Python and scientific-computing libraries such as NumPy, pandas or SciPy.
• Experience translating mathematical or analytical prototypes into production software.
• Strong understanding of algorithms, data structures, software architecture and design principles.
• Experience building automated unit, integration and performance tests.
• Familiarity with numerical methods, floating-point behaviour and numerical validation.
• Experience profiling and optimizing compute-intensive or data-intensive applications.
• Proficiency with Git and modern software-development practices.
• Strong analytical, debugging and problem-solving skills.
• •Ability to work effectively with both researchers and software engineers.

Preferred Qualifications

• Experience with pybind11, Boost.Python, Cython or similar interoperability technologies.
• Knowledge of quantitative finance, portfolio analytics, risk modelling, forecasting or simulation.
• Familiarity with time-series data and financial-market datasets.
• Experience developing applications that process batch or real-time streaming data.
• Exposure to concurrent, parallel or distributed computing.
• Experience with containerization and deployment technologies such as Docker.
• Familiarity with Linux environments, CI/CD pipelines and cloud or on-premises infrastructure.
• Experience building analytical libraries, calculation services or APIs for institutional users.
• Knowledge of Indian financial markets is advantageous

Role Overview

We are looking for experienced Azure Databricks Data Engineers with strong hands-on expertise in Apache Spark/PySpark, Python, SQL, and Azure Data Factory (ADF). The candidate will be responsible for designing, developing, and optimizing scalable data engineering solutions on the Azure cloud platform.

Mandatory Skills

• Strong hands-on experience with Azure Databricks
• Strong knowledge of Apache Spark and/or PySpark
• Proficiency in Python
• Strong SQL development and query optimization skills
• Hands-on experience with Azure Data Factory (ADF)
• Experience developing and maintaining scalable ETL/ELT data pipelines
• Good understanding of Azure data engineering concepts and cloud-based data platforms

Key Responsibilities

• Design, develop, and maintain data pipelines using Azure Databricks and ADF
• Develop efficient data processing solutions using PySpark/Spark and Python
• Write complex SQL queries for data transformation, validation, and analysis
• Build scalable ETL/ELT workflows for large datasets
• Optimize Spark jobs, Databricks notebooks, and data pipelines for performance
• Integrate data from multiple sources into Azure-based data platforms
• Implement data quality, validation, error handling, and monitoring mechanisms
• Troubleshoot production issues and provide timely resolutions
• Collaborate with data architects, analysts, developers, and business stakeholders
• Follow best practices for code quality, security, performance, and maintainability

Experience Requirements

For 5+ Years

• 5+ years of overall experience in data engineering
• Strong hands-on experience in Azure Databricks, PySpark/Spark, Python, SQL, and ADF
• Experience working on enterprise-scale data pipelines

For 9+ Years

• 9+ years of overall experience in data engineering
• Strong expertise in Azure Databricks and modern Azure data engineering
• Proven experience designing and optimizing large-scale data pipelines
• Ability to lead technical discussions and mentor junior engineers

Preferred Skills

• Azure Data Lake Storage (ADLS)
• Delta Lake
• Databricks Workflows
• Azure DevOps / CI-CD
• Git
• Data warehousing concepts
• Experience with Agile/Scrum methodologies

What you'll do

The Software Engineer will serve as a full stack developer within the AI and Automation team, focusing on building AI agents, chatbots, and automation solutions. The role involves taking ownership and accountability to meet commitments, developing software using programming languages, and designing, executing, and reporting on system and service tests to ensure applications function as required. Additional responsibilities include monitoring, diagnosing, and resolving technology issues, as well as supporting team members by carrying out prescribed design activities using established procedures.

What you'll bring

3+ years of experience in full stack application development using Python (for backend) and JavaScript/Typescript (for frontend).

Strong understanding of Java.

Strong understanding of Machine Learning /MLOps using Python .

Familiarity with Agentic AI frameworks.

Familiarity with Kubernetes (K8S) and Docker.

Experience in developing solutions using Azure storage and compute solutions.

Proven experience working with Azure AI solutions, especially AI Foundry and AI Search.

Experience in developing distributed event-driven applications using brokers such as Apache Kafka, IBM MQ, Solace, or Azure Event Hub.

Proven experience in working with DevOps frameworks, GIT, and CI/CD pipelines.

Experience developing integrations using established Enterprise Application Integration patterns and tools such as Apache Camel.

Required Qualifications

Specify the minimum educational qualifications necessary for this role, including degree type, field of study, and level attained.

Applicants should hold a bachelor’s degree in any discipline and possess practical experience in software development. Degrees in Computer Science, Software Engineering, or Information Technology are particularly advantageous. 

Role Overview

The Senior AI/ Machine Learning Engineer will design, build, and optimise the core intelligence layer that powers Cliply’s video understanding and content analysis platform.

This role blends deep hands-on engineering with architectural ownership. You will work across video, audio, and text modalities, shaping model design while also delivering production-ready ML systems. You will be the technical anchor for Cliply’s AI stack, partnering closely with the Lead Architect and the engineering team to bring research concepts into scalable, real-world systems.

Key Responsibilities

Multimodal & Video ML Architecture

• Design and validate deep learning architectures for video, audio, and text understanding, including temporal modelling and multimodal fusion.
• Define approaches for long-sequence modelling, representation learning, and sequence-to-sequence tasks.
• Lead experiments with transformers, vision transformers, video encoders, and hybrid multimodal architectures.

Model Development & Optimisation

• Build and optimise models for content understanding, highlight detection, ranking, and scoring.
• Implement training pipelines, data loaders, augmentations, and evaluation metrics for large-scale video datasets.
• Optimize models for latency, throughput, and GPU efficiency using techniques such as quantization, pruning, distillation, batching, and ONNX/TensorRT.

Production ML Engineering

• Convert prototypes into robust, production-ready services.
• Collaborate with backend engineers to deploy models via scalable APIs and micro-services.
• Monitor model performance in production and design retraining loops for continuous improvement.

Technical Leadership

• Establish best practices for experimentation, evaluation, documentation, and reproducibility.
• Provide mentorship to junior engineers and contribute to Cliply’s long-term AI roadmap.
• Influence architectural decisions across the AI stack to ensure scalability and reliability.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
• 5–10+ years of experience as an ML Engineer, Applied Scientist, or similar role.
• Strong proficiency in PyTorch or TensorFlow, with hands-on experience training deep learning models.
• Deep expertise in multimodal video machine learning,
• Expertise in at least two of the following:

1. Video understanding / video ML
2. Computer vision
3. Speech/audio processing
4. Natural language processing
5. Multimodal fusion

• Experience with GPU training, distributed training, and large-scale datasets.
• Strong understanding of model optimization (quantization, pruning, distillation, ONNX/TensorRT).
• Solid software engineering fundamentals (Python, version control, testing, code review).

Preferred Qualifications

• Experience with multimodal architectures (video-text, audio-text, cross-modal transformers).
• Experience with MLOps tooling (MLflow, Weights & Biases).
• Prior work in startup environments or fast-paced product teams.
• Contributions to open-source ML projects or competitive ML experience (e.g., Kaggle).

Why Join Cliply

• Build the core intelligence layer of a next-generation video understanding platform.
• Own end-to-end architecture and model design - your work becomes the product.
• Work with a founder-led team that values technical excellence, autonomy, and speed.
• Shape the future of multimodal AI in a real product used by creators and enterprises.

About the Role

We are looking for a motivated Data Engineer with 2+ years of professional experience to join our team. You will be responsible for designing, developing, and maintaining scalable data pipelines and cloud-based data solutions while taking ownership across the full software development lifecycle.

The ideal candidate will have strong experience in modern data engineering practices, cloud platforms, and marketing/advertising data integrations such as Google Ads, Meta Ads, and analytics platforms.

This role is suited for someone who enjoys solving complex data challenges, building reliable systems, and working in a fast-paced environment.

Key Responsibilities

• Design, build, and maintain scalable and reliable ETL/ELT data pipelines.
• Develop and optimize data models, transformations, and warehouse solutions for analytics and reporting.
• Work with marketing and advertising datasets from platforms such as Google Ads, Meta Ads, Google Analytics, and similar ecosystems.
• Integrate APIs, third-party systems, and cloud-native services into data workflows.
• Optimize complex SQL queries and improve pipeline performance and reliability.
• Implement data quality checks, monitoring, and observability across pipelines.
• Collaborate with cross-functional teams including product, analytics, and engineering teams to deliver data-driven solutions.
• Contribute to software engineering best practices including Git workflows, CI/CD pipelines, testing, and documentation.
• Participate in architecture discussions and help improve data platform standards and best practices.
• Build and maintain solutions within Google Cloud Platform (GCP) environments.

Qualifications

• 2+ years of professional experience in Data Engineering or related fields.
• Strong proficiency in Python programming.
• Advanced SQL skills with experience in query optimization and data warehousing concepts.
• Experience working with marketing and advertising platforms such as Google Ads, Meta Ads, Google Analytics, DV360, or similar platforms.
• Experience working with AI-assisted coding and development tools such as Claude Code, Cursor, or similar platforms
• Hands-on experience leveraging AI-based development tools to accelerate data engineering implementation and automation
• Familiarity with AI-powered coding assistants and agentic development workflows
• Understanding of marketing data pipelines, attribution reporting, campaign analytics, or customer analytics is highly desirable.
• Hands-on experience with at least one major data engineering technology such as Airflow, Spark, Kafka, Databricks, or similar frameworks.
• Strong experience with Google Cloud Platform (GCP) services such as BigQuery, Cloud Run, Cloud Functions, GCS, or Composer.
• Familiarity with APIs, Linux environments, CLI tools, Git, and CI/CD workflows.
• Strong understanding of data pipeline design, orchestration, monitoring, and troubleshooting.
• Excellent communication, collaboration, and problem-solving skills.
• Ability to work independently and contribute across multiple technical domains.

Who are we?

Inflexion Analytics is a team of data science and analytics consultants based in London, UK, and Bangalore India. Founded in 2015, we have built a strong track record and foundation serving demanding clients. We are now looking to achieve significant growth and become a leading specialist consultancy in the data science field.

What we do?

We help businesses to improve performance through better insight and decision-making. To achieve this, we offer services across the data science value chain including; data strategy, data engineering, data insights, and visual analytics. We work with a global client base, including clients based in the US, UK, Europe, and Australia. 

Data Engineer

Data Lakehouse & Platform Engineering 

About the Role

We are hiring Data Engineer to own the lifecycle of our enterprise Data Lakehouse platform. We are looking for engineers who think in systems, make platform-level design decisions, and can build and operate a production-grade, multi-source lakehouse from the ground up, covering ingestion through consumption across a complex, multi-cloud source landscape.

You will be the technical authority for a platform that consolidates data from 18+ enterprise products (Costpoint, GovWin, Specpoint, Vantagepoint, and others) into a governed, medallion-architected data lake on AWS S3 with Apache Iceberg table format, orchestrated via AWS Step Functions, and queryable through AWS Athena and Trino. This role is end-to-end: you own ingestion, transformation, quality, orchestration, ML data supply, and BI consumption.

Key Responsibilities

•      Architect and evolve the full medallion lakehouse — Bronze, Silver, and Gold layers — on AWS S3 with Apache Iceberg; own schema design, partitioning, compaction, and retention policies.

•      Design and implement scalable Glue ETL (PySpark) pipelines for bronze_to_silver and silver_to_gold transformations, incorporating dbt for SQL-layer transformations where appropriate.

•      Own and extend CDC ingestion via Fivetran; manage schema evolution, connector health, and sync reliability across 18+ source products.

•      Build and maintain AWS Step Functions state machines and EventBridge schedules for end-to-end pipeline orchestration; implement Lambda-based quality and drift monitors.

•      Govern the Glue Catalog and Lake Formation policies; enforce column-level security, row-level access controls, and audit logging to meet SOC2 and regulatory requirements.

•      Architect the query layer — optimize Athena workgroups and partition pruning; plan and execute Trino-on-EKS deployment for sub-second analytics workloads.

•      Partner with data science teams on SageMaker data supply: feature engineering pipelines, training dataset preparation, and model registry integration.

•      Implement real-time and near-real-time streaming solutions using Kafka or Kinesis where sub-13-minute latency is required.

•      Lead platform modernization initiatives: evaluate emerging formats (Iceberg vs. Delta Lake vs. Hudi), tooling, and cost optimization strategies.

•      Establish and enforce data engineering best practices: code reviews, CI/CD for pipeline code, IaC (Terraform / CloudFormation), and incident response runbooks.

•      Mentor and level up junior and mid-level data engineers; define team standards for pipeline design, testing, and documentation.

Required Qualifications

•      Software or data engineering experience, with at least 4 years in an architect or technical lead capacity designing large-scale cloud data platforms.

•      Deep, hands-on expertise with AWS data services: S3, Glue (PySpark ETL), Athena, Step Functions, Lambda, EventBridge, Lake Formation, SageMaker, and CloudWatch.

•      Production experience with Apache Iceberg (or Delta Lake / Hudi) table formats — compaction, snapshot management, schema evolution, and time travel.

•      Strong PySpark and Python skills; ability to write, review, and optimize distributed data processing jobs at scale.

•      Hands-on experience with CDC-based ingestion platforms (Fivetran, Debezium, or equivalent) across heterogeneous source systems.

•      Proven experience designing and implementing medallion (Bronze/Silver/Gold) or equivalent multi-hop lakehouse architectures.

•      Experience with data pipeline orchestration: AWS Step Functions, Apache Airflow, or equivalent; event-driven pipeline design patterns.

•      Strong SQL skills; experience with Athena, Trino, Presto, or equivalent query engines for large-scale analytical workloads.

•      Familiarity with data governance tooling: catalog management (Glue Catalog, Apache Polaris/Iceberg REST), data lineage, access controls, and audit frameworks.

•      Experience with Infrastructure as Code (Terraform or CloudFormation) for data platform provisioning and drift management.

•      Solid understanding of dimensional modeling, schema design (star/snowflake), and data normalization for BI and analytics workloads.

•      Bachelor's degree in Computer Science, Engineering, or a related field; or equivalent professional experience.

Preferred Qualifications

•      Experience operating Trino or PrestoDB on Kubernetes (EKS); tuning for sub-second query latency and multi-tenant workloads.

•      Familiarity with streaming platforms (Kafka, Kinesis, or Pub/Sub) and real-time lakehouse patterns.

•      Experience with Apache Polaris or other Iceberg REST catalog implementations.

•      Exposure to SageMaker MLOps pipelines, Model Registry, and feature store patterns for ML data supply.

•      Experience with dbt (data build tool) for SQL-layer transformation and documentation in lakehouse environments.

•      Government contracting or ERP domain knowledge (Costpoint, Deltek, Oracle, or similar enterprise platforms) is a strong plus.

•      AWS certifications: Data Engineer Associate, Solutions Architect Professional, or equivalent.

What You Will Build

You will be a founding architect of a strategic, cross-product data platform that serves 18+ enterprise applications and their analytics, ML, and AI workloads. The decisions you make on schema, storage format, query layer, governance, and orchestration will shape the data foundation of the company for years. This is a high-impact, high-ownership role with direct visibility to senior leadership.

About the Role:

We are looking for a hands-on Senior Backend Engineer who can own complex product and platform problems end-to-end. You will work across AI agents, workflow orchestration, enterprise integrations, and distributed systems that operate reliably in real-world IT environments.

This role requires strong engineering judgment, product thinking, and the ability to transform ambiguous requirements into scalable, production-ready systems.

Key Responsibilities

• Build the core platform powering agentic IT operations.
• Design reliable multi-step workflows with retries, approvals, rollback mechanisms, and recovery.
• Develop AI pipelines for intent understanding, planning, validation, and execution.
• Build integrations with Microsoft 365, PSA, RMM, and other IT management platforms.
• Design secure, scalable multi-tenant enterprise systems.
• Improve production observability, monitoring, and reliability.
• Own major features from architecture and development through deployment and production support.
• Mentor engineers and contribute to raising the technical standards of the team.

Required Skills & Experience

• 8+ years of experience building backend platforms, distributed systems, or enterprise applications.
• Strong software engineering fundamentals and system design expertise.
• Experience building REST APIs, asynchronous/event-driven systems, databases, and cloud-native applications.
• Strong problem-solving skills with the ability to independently drive solutions in ambiguous environments.
• Excellent debugging, production engineering, and ownership mindset.
• Comfortable using AI coding assistants while independently validating code quality and correctness.

Preferred Technical Stack

Languages & Frameworks

• TypeScript
• Node.js
• Python

Databases & Messaging

• PostgreSQL
• Redis
• Message Queues
• Event-driven architectures

Cloud & Infrastructure

• AWS
• Docker
• Terraform

Enterprise Integrations

• Microsoft Graph API
• Microsoft 365
• OAuth
• Webhooks
• PSA/RMM platforms

AI & Workflow Technologies

• Workflow engines
• State machines
• LLM Agents
• Retrieval-Augmented Generation (RAG)
• AI evaluation frameworks

What We're Looking For

• Strong backend engineering expertise with experience building scalable production systems.
• Deep understanding of distributed systems and platform architecture.
• Ability to own features from design through production.
• Product mindset with strong engineering ownership.
• Excellent collaboration and mentoring skills.

Why Join Neels AI?

• Build the operating layer for the next generation of IT services.
• Work on AI systems that take real-world actions—not just generate text.
• Solve challenging problems across AI, infrastructure, security, and enterprise automation.
• Join at an early stage and influence product direction, architecture, and engineering culture.
• Work directly with experienced founders and global enterprise customers.

Overview

Seeking for an experienced Automation & Reliability Engineering Lead to design, build, and lead automation and metrics solutions that reduce manual support toil and improve operational visibility across Support and SRE teams. This is a hands-on technical leadership role focused on engineering enablement, not tool-specific automation or day-to-day production support.

Key Responsibilities

* Define automation strategy and reference architectures for Support and SRE workflows

* Lead and mentor a small automation engineering team (may start as an individual contributor role)

* Design and build automation utilities, services, and frameworks to eliminate manual operations

* Engineer data pipelines to extract, normalize, and correlate operational data from systems such as Salesforce, email, logs, and internal services

* Define metric semantics (SLAs, lifecycle events, ownership, timestamps) and ensure data accuracy

* Partner with Support, SRE, and Power Platform teams to enable dashboards and reporting

* Establish standards for reliability, error handling, auditability, and documentation in automation solutions

* Identify, prioritize, and track automation opportunities based on toil reduction and risk mitigation

Required Qualifications

* 8+ years of experience in software engineering, automation, or platform engineering

* Strong hands-on programming experience in Python OR Java (one primary language required)

* Proven experience building internal tools, automation frameworks, or backend services

* Solid understanding of APIs (REST), data formats (JSON, CSV), and system integration

* Experience working with operational or production systems and understanding support workflows

* Ability to translate business or operational needs into reliable engineering solutions

Preferred Qualifications

* Experience designing or contributing to automation programs at scale

* Familiarity with observability concepts such as logging, metrics, and alerting

* Working knowledge of SQL or data persistence technologies

* Prior experience collaborating with SRE, DevOps, or Support teams

Nice to Have

* Exposure to AI/ML or GenAI techniques applied to operational automation (classification, summarization, anomaly detection)

* Experience supporting metric pipelines feeding BI or workflow automation platforms

* Healthcare or SaaS domain experience

Position: Computer Vision Engineer

Experience: 2–3 Years

Location: Bengaluru, Karnataka

Employment Type: Full-time

About the Role

We are seeking a highly motivated Computer Vision Engineer to join our autonomy and avionics team. The role involves developing, implementing, and validating computer vision models and algorithms and pipelines for UAVs operating in both GNSS-available and GNSS-denied environments.

The ideal candidate should have a strong foundation in theory of deep learning and machine learning, strong understanding of electromagnetic spectrum, imaging fundamentals, camera principles, and mathematical concepts with hands-on experience in implementing these algorithms on embedded or real-time systems.

Key Responsibilities

• Design, develop, and optimise AI Models
• Make custom CNNs/ modify existing CNNs to suit specific problems at hand
• Handle end-to-end training flow
• Implement end to end inference pipelines on standard PCs as well as on embedded systems
• Understand performance benchmarks and assess the accuracy and inference times
• Implement traditional image processing algorithms
• Factor the code to leverage underlying hardware architecture
• Prune the networks for efficiency
• Integrate the system within the application framework using C++
• Work closely with perception, controls, embedded software, and systems engineering teams.

Required Qualifications

• B.E./B.Tech/M.E./M.Tech in Computer Science and Engineering, Electronics, ECE, Mechatronics, or a related discipline.
• 2–3 years of experience in relevant area
• Strong understanding of: Linear Algebra, Probability and Statistics, AI-ML-DL fundamentals, Image processing, Camera Functioning
• Strong programming skills in C++ and Python.
• Experience with MATLAB for algorithm development and validation.
• Familiarity with Linux development environments.
• Experience with Git version control.

Preferred Skills

• Experience with Camera, IMU Calibration and Synchronisation
• Experience with multi-sensor fusion.
• Experience working with NVIDIA devices
• Experience on FPGA will be an added advantage
• Full understanding of Git functionality
• Exposure to airborne software development processes and coding standards (e.g., MISRA C++).

Personal Attributes

• Strong analytical and problem-solving skills.
• Ability to work independently on challenging technical problems.
• Good communication and documentation skills.
• Passion for solving challenging problems
• Willingness to participate in field trials and flight testing.
• Team playwe

 Job Description:

• Job title : Senior DevOps Engineer (On-Premises Automation)        
• Experience: 8+ years
• Location: Chennai / Pune / Hyderabad / Bangalore
• Shift: UK Shift
• Work Mode: Onsite (WFO)

Roles and Responsibilities:

• This engagement automates end-to-end infrastructure build provisioning across on-prem and Azure. The team will build a shared ServiceNow-led intake, approval, orchestration, and closed-loop status model, using Jenkins/Ansible for on-prem builds and Azure DevOps/Terraform for cloud builds. Automation includes standards, security/compliance controls, scan gates, CMDB/change updates, and handover.              

Key Responsibilities:

• Lead secure and repeatable on-prem build provisioning pipelines
• Lead Jenkins CI/CD for automated on-prem provisioning and configuration.
• Create pipeline templates for VM/physical host, OS deployment, configuration, certification, and rollback.
• Embed hardened-image validation, scan gates, secrets handling, approvals, and audit evidence.
• Lead Ansible roles, PowerShell modules, test automation, and code reviews.
• Implement logging, monitoring, and root-cause analysis; support UAT and hypercare.       

Required Qualifications:

• 8–10 years in DevOps, platform engineering, or infrastructure automation.
• Bachelor’s degree or equivalent experience.
• Jenkins
• Git, CI/CD
• Ansible, PowerShell
• Python, IaC
• security scanning, secrets management
• Windows/Linux.

AI Engineer

LLMs, Agents & AI Services

📍 Mumbai (On-site) | Full-time | 2-4 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

AI is core to how we design, deliver, and scale software for our customers.

We are hiring an AI Engineer for a dedicated client engagement building a complex production AI platform, working on the AI capabilities and agentic features at the core of the product.

The mandatory requirement for this role is at least one AI feature personally shipped to production for real users, with operational ownership.

The role suits someone who thinks quickly on solutioning, can take an ambiguous problem to a working prototype in days, and has the discipline to carry it through to production with predictable economics.

You will work alongside the Senior AI Engineer and the wider pod, with ownership of parts of the AI surface area of the product.

Responsibilities:

Solutioning and POCs

Translate ambiguous customer problems into working POCs at speed.

Pick the right model, framework, and architecture, and demonstrate value early before scaling investment.

LLM Application Development

Build AI features and services using LLM APIs from OpenAI, Anthropic, Google, and self-hosted open-weight models (Llama, Qwen, Mistral).

Choose the right model per use case based on cost, latency, capability, and context-window trade-offs.

Agentic System Design

Design and implement agentic workflows using LangGraph, CrewAI, AutoGen, LlamaIndex Agents, or custom orchestration.

Cover tool use, planning, memory, and multi-step reasoning appropriate to the problem.

API and Service Development

Build production AI services and APIs using Python and FastAPI.

Handle streaming responses, async processing, structured outputs, retries, and graceful degradation when models or tools fail.

Retrieval and Tool Integration

Implement RAG pipelines with vector databases (Pinecone, Weaviate, Qdrant, pgvector, Chroma), embeddings, chunking strategies, hybrid search, and reranking.

Integrate external tools, internal APIs, and document sources through tool-calling and MCP-style patterns.

Cost Analysis and Unit Economics

Model the per-request and per-user cost of every AI feature before it ships.

Track token usage, prompt caching, batching, and model-routing strategies.

Drive measurable improvements in unit economics.

Production Hardening

Add observability and tracing (LangSmith, Langfuse, OpenTelemetry), guardrails, content safety checks, prompt injection defences, and fallback behaviour.

Prompt Engineering and Evaluation

Design, test, and iterate prompts with measured outcomes.

Build evaluation harnesses for accuracy, hallucination, latency, and cost.

Run benchmarks across models and prompt variants before locking in a design.

Requirements:

AI Feature Shipped to Production (Mandatory)

Must have personally built and shipped at least one AI feature that runs in production for real users, with operational ownership.

POCs, internal demos, and one-off scripts do not qualify.

2 to 4 Years of Professional Software or AI Engineering Experience

With at least one production AI feature owned end to end.

Strong Python Proficiency and API Development with FastAPI

Comfort with type hints, async, packaging, testing, streaming responses, and authentication.

Production-grade Python, not notebook-only code.

Hands-on Depth Across the LLM and Agent Stack

Working experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or self-hosted open-weight models (vLLM, Ollama, Together, Replicate).

Working familiarity with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.

Working knowledge of RAG, embeddings, and vector databases (Pinecone, Weaviate, Qdrant, pgvector, Chroma).

Solutioning Speed and POC Velocity

Demonstrated ability to move from a fuzzy problem to a working prototype in days.

Strong instinct for what to build first, what to defer, and what to throw away.

Cost Discipline for Production AI

Ability to calculate, monitor, and optimise the cost of LLM APIs, tokens, embeddings, vector store usage, and infrastructure.

Treats unit economics as a first-class concern.

AWS Familiarity

Working knowledge of EC2, S3, IAM, and at least one of Bedrock, SageMaker, or equivalent.

Comfortable in a Fast-Moving Environment

Self-directed, comfortable with ambiguity, takes ownership without being asked, and ships under shifting priorities.

Strong Written and Spoken English Communication

Able to explain trade-offs to non-AI engineers, designers, product managers, and clients in plain language.

Nice to Have

• fine-tuning or LoRA, QLoRA, PEFT exposure
• MCP server authoring
• eval framework experience (LangSmith, Promptfoo, Ragas, DeepEval)
• open-source AI contributions
• multi-modal models (vision, audio)

Job Summary

We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.

Technical Skills

• Strong hands-on experience in Python and PySpark development.
• Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
• Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
• Experience with Power BI Data Modeling and Semantic Layer development.
• Proficiency in DAX (Data Analysis Expressions).
• Experience designing and managing Semantic Models in Power BI.
• Strong SQL skills and experience working with large datasets.
• Knowledge of data warehousing concepts and best practices.

Preferred Skills

• Experience with cloud platforms such as Azure, AWS, or GCP.
• Exposure to modern data platforms like Databricks.
• Understanding of data governance and data quality frameworks.

About the Company

The client is revolutionising the way businesses operate through cutting-edge technological solutions. Their focus is on developing intelligent agents and agentic workflows that automate processes and eliminate the need for human effort wherever possible. By leveraging

advanced AI and machine learning, they create systems that enhance productivity and drive efficiency.

Their expertise extends to the fintech, healthcare and medical technology sectors, where they develop innovative solutions that improve patient outcomes and streamline medical operations.

From medical devices to healthcare platforms, their work sits at the intersection of technology and medicine, pushing the boundaries of what's possible. The team is dedicated to continuous learning and growth, ensuring the team members are always at the forefront of the tech landscape.

About the Role

This is a senior, hands-on engineering role at the heart of our product team. You will be one of the most technical people in the room — setting the architecture for our real-time voice AI

agents and building the hardest parts of it yourself. From the systems that power live conversations to the interfaces our clients rely on, you will own how the product is engineered end to end.

We are looking for a genuine lead full-stack engineer with the depth to make architecture decisions that hold up as we scale, and the appetite to still be in the code every day. You should be as comfortable designing the backend services behind a live voice agent as you are shaping a clean interface on top of them — and comfortable being the person others turn to when something is hard.

You will work directly with the founder and product leadership on a fast-moving product, with real influence over technical direction. This is a role for someone who wants ownership at the level of "how the whole thing is built," not just individual features — and who raises the bar for

everyone around them.

What You'll Own

Set the technical direction

• Own the architecture of our core systems — the real-time voice agents, backend
• services, data and APIs — making the decisions that keep the product fast, reliable and scalable as it grows.
• Lead the hardest engineering problems and solve them personally.
• Establish engineering standards — code quality, review practices, testing and technical patterns that the team builds to.
• Drive technical strategy with the founder and product leadership — shaping the roadmap, flagging risk early, and turning product ambition into a sound technical plan.

Build the product end to end

• Design, build and ship features across the stack — backend services, APIs and front-ends — owning them from idea to production.
• Build the client-facing surfaces — dashboards, review tools and configuration interfaces that let our clients run and trust the product.
• Design and evolve the data models and APIs that hold up as we scale across clients.

Make it reliable and fast

• Own production quality — put the monitoring and alerting in place so issues are caught before clients feel them, and performance stays within target.
• Care about performance — find and fix bottlenecks across the stack.
• Build for correctness — put the testing and evaluation in place that keeps the product behaving predictably as it changes.

Lead through the team

• Mentor and grow engineers — through code review, pairing, and setting a technical example others learn from.
• Multiply the team's output — unblock others and lift the overall quality of the codebase.
• Take features from ambiguity to done — turn a rough product goal into a shipped, working capability with minimal hand-holding, and help others do the same.

What We're Looking For

• 8+ years of professional software engineering experience, with significant depth across both backend and frontend and a track record of owning systems, not just features.
• Strong backend engineering, ideally in Python — building and scaling production services and APIs.
• Strong frontend engineering with a modern framework such as React — able to architect and build polished, responsive interfaces independently.
• Proven architecture and system-design ability — you have designed systems that scaled, and can reason clearly about trade-offs.
• Solid fundamentals across APIs, databases and cloud infrastructure.
• Experience building real-time and/or AI-powered products — or clear, demonstrable ability to lead in this area.
• A history of technical leadership — setting standards, mentoring engineers, and being trusted with the hardest problems — while remaining hands-on.
• Excellent communication and a genuine ownership mindset — someone who can be handed an ambiguous, high-stakes problem and be trusted to see it through.

Nice to Have

• Experience working with AI / large language models in production.
• Experience with voice or other real-time products.
• Exposure to healthcare, fintech, or other regulated / high-stakes domains.
• Experience as an early or senior engineer in a startup, where you set direction and wore many hats.

Company Description

Appiness Interactive Pvt. Ltd. is a Bangalore-based product development and UX firm that

specializes in digital services for startups to fortune-500s. We work closely with our clients to

create a comprehensive soul for their brand in the online world, engaged through multiple

platforms of digital media. Our team is young, passionate, and aggressive, not afraid to think

out of the box or tread the un-trodden path in order to deliver the best results for our clients.

We pride ourselves on Practical Creativity where the idea is only as good as the returns it

fetches for our clients.

About the Role

You will own the reliability of the distributed data systems, the streaming runtime and

processing engines that move hundreds of billions of rows per day for top-tier enterprises. This

is an SRE role for our big data stack: Kafka, Spark, Flink, Ray, Redis, and data warehouses, all

running on Kubernetes.

This is not a cloud-provisioning role. We are looking for someone who has lived inside stateful,

high-throughput systems in production who has chased down a broker outage, a checkpoint

stall, a crashlooping cache, and a sink that silently stopped writing, and who fixes the

architecture rather than the symptom. If keeping a large, busy data platform alive and fast is the

kind of problem you find satisfying, you will have a lot of fun working with us. This is a unique

opportunity to shape the foundation of a product that is defining the next wave of intelligent,

context-aware data movement.

Responsibilities

● Streaming & Data Plane Reliability: Own the health of our Kafka-based runtime

(managed via Strimzi on Kubernetes) - broker health, topic lifecycle and count

management, partition and throughput tuning, certificate/secret rotation, and version

upgrades - at a scale of hundreds of thousands of topics and hundreds of billions of rows

per day.

● Distributed Processing Engines: Operate and tune distributed system workloads in

production in collaboration with backend teams, resource allocation, autoscaling,

checkpointing, backpressure, and failure recovery for both batch and streaming jobs.

● Stateful Services: Run Redis clusters and other stateful systems reliably - failover,

persistence, liveness/readiness tuning, and capacity planning under heavy and bursty

load.

● Kubernetes & Operators: Take end-to-end ownership of Amazon EKS, Google GKE and

the operators (Strimzi and others) running our stateful data workloads - cluster lifecycle,

scaling, version upgrades, and resource governance.

● Observability: Build deep, data-aware monitoring - consumer lag, throughput, partition

skew, job latency, error rates - not just host and CPU metrics. Make the data plane's

behavior legible before it breaks.

● Incident Management: Lead root-cause analysis for distributed-systems failures (broker

outages, crashloops, sink decommissions, control-plane race conditions) and drive

durable fixes. Mitigate fast, but design out the recurrence.

● Infrastructure as Code & Automation: Provision and manage cloud infrastructure with

Terraform; build operational runbooks and automation, including for air-gapped/private

enterprise installs (pre-staged images, operator-facing procedures).

● Collaboration: Partner with platform, runtime, and connector engineering - and with

SREs and support - to ship and scale new data-movement features reliably in a

large-scale Linux environment.

Qualifications

● Experience: 6+ years in infrastructure, SRE, or DevOps, with significant time spent

operating production distributed data systems (not just application/cloud infra).

● Kafka: Deep, hands-on operational experience running Kafka at scale in production -

ideally on Kubernetes via Strimzi - including upgrades, topic/partition management,

performance tuning, and TLS/secret rotation.

● Distributed Processing (Strong Plus): Production experience operating one or more of

Spark, Flink, or Ray - resource tuning, checkpointing, failure recovery.

● Stateful Systems (Must Have): Production experience with Redis (clustering, persistence,

failover) and a solid understanding of operating stateful workloads on Kubernetes

(StatefulSets, PVCs, probes, operators).

● Data Warehouses: Familiarity operating against Snowflake, BigQuery, or similar, and an

understanding of JDBC connectivity and sink reliability.

● Kubernetes & EKS: Strong hands-on EKS cluster creation, scaling, version upgrades, and

operator management.

● Infrastructure as Code: Advanced proficiency with Terraform.

● Programming: Proficiency in Python (or similar) for automation and tooling. Comfort

reading and debugging JVM-based systems is a strong plus.

● Reliability Mindset: Demonstrated ownership of incident management, RCA, capacity

planning, and performance tuning for high-throughput systems.

● CI/CD: Solid understanding of CI/CD methodology (Jenkins, GitHub Actions, or GitLab CI)

for containerized and non-containerized apps. Supporting, not the core of the role.

● Nice to Have: Configuration management (Ansible preferred); broader AWS services

(IAM, VPC, EC2, S3, Lambda); AWS CloudFormation.

● Soft Skills: Excellent communication and organizational skills; ability to coordinate

effectively within a team and with customers.

Why This Might Be Worth It

● You own the hard part. The stateful, distributed systems that move billions of rows are

the platform's most demanding reliability problems - and they'd be yours.

● Impact at scale from day one. Your work keeps mission-critical data flowing for

companies like DoorDash and LinkedIn.

● The AI wave is real for us. We're not bolting AI onto a legacy product. Intelligent

connectors, context-aware data movement, and agentic workflows are the core of what

we're building next - on top of the runtime you'd run. ○ Small team, big problems. Direct

access to the CTO, real influence over product direction, and the autonomy to make

significant technical bets. ○ Recognized platform, startup energy. Enterprise validation

with the speed and ownership of an early-stage company.

Role Summary

Seeking an experienced SQL Developer with strong expertise in Data Lake architecture, Data Engineering, AI/ML data modelling, and Vector Database design. The candidate will be responsible for building scalable data platforms, developing optimized SQL solutions, designing AI-ready data models, and supporting enterprise analytics and GenAI initiatives.

Key Responsibilities

• Design, develop, and optimize complex SQL queries, stored procedures, views, and database objects.
• Build, maintain, and govern enterprise Data Lakes for structured, semi-structured, and unstructured data.
• Design scalable data models for Analytics, Machine Learning (ML), and AI applications.
• Develop and maintain data ingestion, transformation, and data preparation pipelines.
• Architect and manage Vector Database solutions supporting GenAI, semantic search, embeddings, and RAG-based applications.
• Ensure data quality, security, performance, governance, and scalability across platforms.
• Integrate data from multiple enterprise systems, databases, APIs, and business applications.
• Collaborate with Business, Analytics, Data Science, and AI teams to deliver enterprise data solutions.

Mandatory Skills

• Advanced SQL Development (SQL Server, PostgreSQL, Oracle, MySQL, etc.)
• Data Lake Architecture, Development, and Maintenance
• Data Warehousing & Dimensional Data Modelling
• AI/ML Data Modelling and Feature Engineering
• Python for Data Engineering, Data Processing, and Automation
• Query Performance Tuning & Database Optimization
• Data Governance & Data Quality Management
• Vector Database Architecture and Management (Pinecone, Qdrant, Weaviate, Milvus, Chroma, or similar)
• Experience handling large-scale structured and unstructured datasets

Preferred Skills

• Experience with GenAI, RAG (Retrieval-Augmented Generation), Embeddings, and LLM-based applications
• PySpark and Distributed Data Processing
• Power BI or Enterprise Reporting Platforms
• Knowledge of MLOps, AI data pipelines, and modern data architectures

Key Attributes

• Strong analytical and problem-solving skills
• Ability to independently own end-to-end data platform solutions
• Excellent communication and stakeholder management skills
• Passion for Data Engineering, AI, ML, and GenAI technologies

Ideal Candidate

A hands-on SQL Developer who can build and maintain enterprise Data Lakes, design AI/ML-ready data models, develop Python-based data solutions, and architect Vector Database platforms to support advanced analytics, AI, and GenAI initiatives.