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SENIOR PYTHON DEVELOPER

Designation: Senior Python Django Developer 

Position: Senior Python Developer

Job Types: Full-time, Permanent

Pay: Up to ₹800,000.00 per year

Schedule: Day shift (On-site)

Supplemental Pay: Performance bonus, Yearly bonus

Ability to commute/relocate:  JP Nagar, Bangalore: Reliably commute or willing to relocate with an employer-provided relocation package (Preferred)

Experience: Back-end development: 5 years (Required)

Job Description:

We are looking for a highly skilled Senior Python Django Developer with extensive experience in building and scaling financial or payments-based applications. The ideal candidate has a deep understanding of system design, architecture patterns, and testing best practices, along with a strong grasp of the startup environment.

This role requires a balance of hands-on coding, architectural design, and collaboration across teams to deliver robust and scalable financial products.

Responsibilities:

• Design and develop scalable, secure, and high-performance applications using Python (Django framework).
• Architect system components, define database schemas, and optimize backend services for speed and efficiency.
• Lead and implement design patterns and software architecture best practices.
• Ensure code quality through comprehensive unit testing, integration testing, and participation in code reviews.
• Collaborate closely with Product, DevOps, QA, and Frontend teams to build seamless end-to-end solutions.
• Drive performance improvements, monitor system health, and troubleshoot production issues.
• Apply domain knowledge in payments and finance, including transaction processing, reconciliation, settlements, wallets, UPI, etc.
• Contribute to technical decision-making and mentor junior developers.

Requirements:

• 5 to 10 years of professional backend development experience with Python and Django.
• Strong background in payments/financial systems or FinTech applications.
• Proven experience in designing software architecture in a microservices or modular monolith environment.
• Experience working in fast-paced startup environments with agile practices.
• Proficiency in RESTful APIs, SQL (PostgreSQL/MySQL), NoSQL (MongoDB/Redis).
• Solid understanding of Docker, CI/CD pipelines, and cloud platforms (AWS/GCP/Azure).
• Hands-on experience with test-driven development (TDD) and frameworks like pytest, unit test, or factory boy.
• Familiarity with security best practices in financial applications (PCI compliance, data encryption, etc.).

Preferred Skills:

• Exposure to event-driven architecture ( 
• Experience integrating with third-party payment gateways, banking APIs, or financial instruments.
• Understanding of DevOps and monitoring tools (Prometheus, ELK, Grafana).
• Contributions to open-source or personal finance-related projects.
•  

Job Summary

We are seeking a highly skilled GCP Data Engineer with strong expertise in Google Cloud Platform (GCP), Python, ETL, and modern data engineering technologies. The ideal candidate should have hands-on experience designing and building scalable data pipelines using BigQuery, Dataflow, Pub/Sub, Airflow, and modern data lake technologies such as Apache Iceberg or Delta Lake.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines on Google Cloud Platform.
• Build and optimize data processing workflows using Python and Google Cloud Dataflow (Apache Beam).
• Develop and manage large-scale analytical data models in BigQuery.
• Implement event-driven data ingestion using Google Cloud Pub/Sub.
• Create, schedule, and monitor workflows using Apache Airflow and Autosys.
• Design and implement modern data lake architectures using Apache Iceberg or Delta Lake.
• Optimize query performance, storage, and compute costs in GCP.
• Ensure data quality, governance, security, and compliance across data platforms.
• Collaborate with Data Scientists, Analysts, and Application teams to deliver scalable data solutions.
• Troubleshoot production issues and continuously improve pipeline reliability and performance.

Mandatory Skills

• Strong hands-on experience with Google Cloud Platform (GCP).
• Proficiency in Python programming.
• Experience in designing and implementing ETL/ELT pipelines.
• Strong knowledge of BigQuery.
• Experience with Google Cloud Dataflow (Apache Beam).
• Experience with Google Cloud Pub/Sub.
• Hands-on experience with Apache Airflow.
• Experience in job scheduling using Autosys.
• Experience with modern table formats such as Apache Iceberg or Delta Lake.
• Strong SQL and data modeling skills.

Preferred Skills

• Experience with Cloud Storage, Dataproc, Cloud Composer, and Cloud Functions.
• Knowledge of CI/CD pipelines and DevOps practices.
• Experience with Docker and Kubernetes.
• Familiarity with Git and Agile/Scrum methodologies.
• Knowledge of data warehousing and dimensional modeling.
• Exposure to streaming and real-time data processing.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
• 4–8+ years of experience in Data Engineering with hands-on expertise in GCP technologies.

Required Experience

• Strong experience in developing enterprise-grade data pipelines using Python and GCP.
• Hands-on experience with BigQuery, Dataflow, Pub/Sub, and Airflow.
• Experience scheduling and monitoring batch workflows using Autosys.
• Experience implementing modern data lake architectures using Apache Iceberg or Delta Lake.
• Strong understanding of ETL best practices, performance tuning, and data optimization.
• Excellent analytical, troubleshooting, and problem-solving skills.

Mandatory Skills

• Google Cloud Platform (GCP)
• Python
• ETL
• BigQuery
• Autosys
• Apache Airflow
• Google Cloud Pub/Sub
• Google Cloud Dataflow (Apache Beam)
• Apache Iceberg / Delta Lake
• SQL & Data Modeling

We are looking for a skilled Python & PySpark Developer with strong expertise in Big Data technologies, Spark, SQL/PL-SQL, and REST API development using Flask or Django. The ideal candidate should have experience building scalable data pipelines, processing large datasets, developing APIs, and working with distributed computing frameworks.

Key Responsibilities

• Develop, optimize, and maintain scalable data pipelines using PySpark and Apache Spark.
• Design, develop, and optimize complex SQL and PL/SQL queries, stored procedures, functions, and database objects.
• Build and maintain RESTful APIs using Flask or Django.
• Develop robust Python applications for data engineering and backend services.
• Process and analyze large-scale datasets using Big Data technologies.
• Optimize Spark jobs for performance, scalability, and reliability.
• Integrate APIs with internal and external systems.
• Collaborate with cross-functional teams including Data Engineers, Data Scientists, and Application Developers.
• Troubleshoot production issues and implement performance improvements.
• Follow coding standards, version control, and CI/CD best practices.

Mandatory Skills

• Strong proficiency in Python programming.
• Hands-on experience with PySpark and Apache Spark.
• Strong SQL coding skills.
• Experience with PL/SQL development.
• Experience in Big Data ecosystem.
• REST API development using Flask or Django.
• Experience in developing and consuming Python APIs.
• Knowledge of data processing, ETL, and distributed computing.
• Experience with Git/version control.

Preferred Skills

• Experience with Hadoop ecosystem (Hive, HDFS, YARN).
• Exposure to cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Airflow or other workflow orchestration tools.
• Experience with Docker and Kubernetes.
• Familiarity with Kafka or other streaming technologies.
• Understanding of CI/CD pipelines.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
• 4–8+ years of experience in Python and Big Data development (can be adjusted based on the role).

Required Experience

• Strong hands-on experience in Python, PySpark, and Apache Spark.
• Extensive experience writing optimized SQL and PL/SQL code.
• Experience developing REST APIs using Flask or Django.
• Experience working with large-scale data processing and ETL pipelines.
• Strong analytical, debugging, and problem-solving skills.

Mandatory Skills: Python, PySpark, SQL Coding, Apache Spark, Big Data, Flask/Django (REST API), PL/SQL, Python APIs.

Agent Application Engineer (Backend / Agentic AI) — Level 1

About Sentiaflow

Sentiaflow is an AI engineering and IT services company that designs and delivers production-grade agentic AI systems. We work at the point where large language models meet real business operations: data, APIs, permissions, workflow state, human decisions, security, evaluation, and measurable outcomes.

Our initial domain focus is healthcare, particularly clinical trials and related operational workflows. These are environments where an impressive demo is not enough. A system must be dependable, traceable, appropriately controlled, and clear about when a human must make the decision.

We are building a specialised engineering organisation across three disciplines:

• Agent Application Engineering
• Agent Platform & Evaluation Engineering
• Applied AI & Model Engineering

The Role

We are hiring strong backend or application engineers who want to specialise in building agentic AI applications. You do not need to arrive with several years of "agent engineer" experience. We are more interested in whether you have built real software, understand how production systems fail, and can learn to use models inside controlled business workflows.

As a Level 1 Agent Application Engineer, you will implement bounded parts of a production workflow under the guidance of an Agent Captain or senior engineer. Your work will connect models to application services, tools, data sources, and human approval points. You will be expected to make every important step observable, testable, and recoverable.

This is not a prompt-writing position, and it is not a generic chatbot role. It is an application engineering role for systems in which some decisions are probabilistic, while the surrounding controls must remain deterministic.

What You Will Work On

The specific client problem will vary, but typical work may include:

• Converting a clinical-operations signal into a bounded workflow that gathers evidence, analyses likely causes, presents options, and routes a recommendation to an authorised person.
• Building services that extract or structure information from trial documents and pass the result through validation and human review.
• Integrating agent workflows with internal APIs, databases, document systems, notification services, and client platforms.
• Implementing workflow state, recovery behaviour, approval gates, permissions, traceability, and scenario-based evaluations.

The work concerns operational decision support and workflow execution. It does not delegate clinical judgment or patient-care decisions to an autonomous model.

What You Will Be Responsible For

• Translate a clearly scoped business workflow into typed inputs, outputs, states, actions, and escalation paths.
• Build reliable application services and tool integrations using Node.js/TypeScript or Python.
• Use an LLM only where model judgment adds value; implement rules, validation, authorisation, and workflow control in deterministic code.
• Design structured model outputs and validate them before they can affect downstream systems.
• Handle partial data, unavailable tools, duplicate events, retries, time-outs, rate limits, and other normal production failure modes.
• Add logging, traces, metrics, and decision records that make the workflow diagnosable.
• Create tests and evaluation cases that measure whether the complete workflow behaves correctly—not merely whether an answer sounds fluent.
• Protect sensitive information and participate in code, design, failure-analysis, and release-readiness reviews.
• Explain your implementation and its trade-offs clearly to engineers, delivery leads, and client stakeholders.

At Level 1, you will not be expected to define the entire client architecture alone. You will be expected to own your assigned module, ask precise questions, surface risks early, and bring it to a production-ready standard with senior review.

What We Are Looking For

Essential Experience

• Approximately 3–6 years of hands-on backend or application engineering experience.
• Evidence that you have built or materially owned production APIs, services, data flows, integrations, or workflow-heavy applications.
• Strong programming ability in JavaScript/TypeScript, Python, Java, C#, Go, or a comparable backend language. Our preference is Node.js/TypeScript, but engineering depth matters more than language loyalty.
• Practical understanding of API design, databases, asynchronous processing, authentication and authorisation, testing, and deployment.
• Ability to reason clearly about state, retries, idempotency, concurrency, permissions, audit trails, and failure recovery.
• Experience debugging real production behaviour rather than only building greenfield demonstrations.
• Clear written and verbal communication, including the ability to explain technical trade-offs without hiding behind framework terminology.

Useful, but Not Mandatory

• Experience integrating LLM or machine-learning capabilities into an application.
• Experience with event-driven systems, state machines, workflow engines, observability, evaluation harnesses, or production incident analysis.
• Experience in healthcare, life sciences, clinical trials, or another regulated or audit-sensitive environment.

Healthcare or clinical-trials experience is preferred, not required at Level 1. We would rather hire a strong production engineer who can learn the domain than a candidate who knows the vocabulary but cannot build dependable systems.

What Does Not Qualify by Itself

Any of the following may be useful experience, but none is sufficient on its own:

• A chatbot or "chat with your documents" application.
• A RAG demonstration built primarily by connecting frameworks.
• A list of AI tools, model names, courses, certificates, or prompt-engineering techniques.
• An application that works in a demo but has no clear handling of permissions, failures, evaluation, or production operations.

How We Will Assess Fit

Our evaluation is designed to identify engineering judgment without asking you to build unpaid project work. We will focus on:

• A structured discussion of a production system you have worked on.
• Questions grounded in your own CV and claimed experience.
• A realistic workflow scenario covering system boundaries, evidence, controls, failure modes, and testing.
• Backend fundamentals and how you would apply them to an AI-enabled workflow.

You are NOT expected to have built a clinical-trials agent before applying.

What Success Looks Like

Within your first six months, you should be able to:

• Implement a bounded agent-workflow module from an agreed design and take responsibility for its quality.
• Integrate models and tools without allowing probabilistic output to bypass deterministic controls.
• Produce traces, tests, and evaluation evidence that support a release decision.
• Diagnose failures across application, tool, data, and model boundaries with progressively less supervision.
• Explain the workflow to a client or domain stakeholder in clear operational language.

Consistent performance at this level creates a path towards Level 2 — Independent Delivery Engineer, where you own a production workflow end to end, including discovery, architecture, integrations, evaluation, failure handling, and release readiness.

Why You Should Join Us

• Build the real systems behind agentic AI. You will work beyond demos and wrappers on the engineering problems that determine whether an AI workflow can operate in production.
• Develop a scarce, durable specialisation. Sentiaflow offers a defined progression across application engineering, platform and evaluation, and applied AI—not a vague instruction to "learn AI."
• Work on consequential operational problems. Clinical-trials workflows demand evidence, traceability, human accountability, and reliable execution.
• Learn through delivery with experienced review. You will own meaningful engineering work while receiving architectural and domain guidance appropriate to your level.
• Influence how the discipline is built. We are at an early stage, so strong engineers will help shape our methods, reusable assets, quality standards, and engineering culture.

About the Role

CLOUDSUFI, a Google Premium Partner specializing in data and AI solutions, is seeking a Staff / Principal Tech Lead to drive the technical execution of our Google Data Commons program. This is a high-visibility, horizontal leadership role embedded within the Google ecosystem — based physically at Google's Bangalore office — working in close daily collaboration with Google's core Data Commons engineering team. The Tech Lead is the technical spine of the engagement. They sit across all four delivery areas — Data Engineering, Frontend, ML/AI, and DevOps/Infrastructure — providing architectural direction, resolving cross track dependencies, and ensuring the quality and coherence of everything we ship. Equally critical is the ability to represent CloudSufi in a credible, articulate, and collaborative manner to Google counterparts at every level.

This is a genuinely hands-on role: the successful candidate must be able to write, debug, and reason about Python and GCP code themselves — not only direct others or lean on AI coding assistants — and must be comfortable operating in an open-source, public-data environment without relying, for example, on Google internal (google3) tooling.

Technology Stack & Domain Knowledge

Core / Must-Have

• Relevant experience on Knowledge Graph, Statistical Data and Analytics (any experience with Google Data Commons is a nice to have, but not required)

• Google Cloud Spanner – schema design, distributed transactions, interleaved tables, and performance tuning at scale.

• Google BigQuery – data modeling, partitioning/clustering strategies, query optimization, and integration with downstream consumers.

• Data pipelines – Apache Beam / Dataflow, or equivalent GCP-native ETL tooling.

• Infrastructure as Code – Terraform on GCP; Cloud Build, Artifact Registry, GKE or Cloud Run.

• Demonstrable, autonomous hands-on proficiency in Python and native GCP tooling — able to code and debug independently in a live technical discussion, with AI-assisted development as a complement to (not a replacement for) that proficiency.

• Direct experience working with open, public, and unstructured datasets (e.g. sourcing, cleaning, and integrating public statistics or open data feeds) using open-source or standard GCP-native tooling.

• Solid grounding in knowledge graph vs data warehouse principles, and how to design for schema and data drift in an open-source knowledge graph context.

• CI/CD experience and working with GitHub

• Full stack experience, specially with data centric apps/systems Strong Advantage

• Python (primary language for Data Commons import tooling and ML pipelines).

• TypeScript / React for the Data Commons web frontend and visualization layers.

• Vertex AI, BigQuery ML, or equivalent ML lifecycle tooling.

• Knowledge graph principles, RDF/SPARQL, or statistical data modeling.

• DataCommons Python / REST APIs and the DCID import automation tools.

• Experience with Google's internal engineering culture, tools (e.g. Buganizer, Critique, Cider), or prior delivery inside a Google product or partnership engagement.

Experience & Qualifications Required

• 10+ years of software engineering experience, with at least 3 years in a formal or informal tech lead capacity overseeing multiple workstreams.

• Demonstrable experience delivering production-grade systems on Google Cloud Platform.

• Prior experience working with or for Google — as a Googler, through a Google partnership program, or as a contractor embedded in a Google team — is strongly preferred.

• Exceptional verbal and written English communication skills; able to engage confidently with senior Google engineers and program managers.

• Proven ability to operate across ambiguous, fast-moving programs with multiple parallel tracks.

• Based in Bangalore, India, and able to work on-site at Google's Bangalore office on a regular basis.

• Able to read and interpret an RFP / SOW and connect its terms to a workable technical delivery plan. 

Key Responsibilities

Data Modeling & Power BI Development

Design, develop, and maintain high-performance Power BI dashboards and reports.

Build robust, scalable data models using **advanced DAX (Data Analysis Expressions)** to implement complex business logic, time-intelligence calculations

Optimize existing reports and data models for speed, efficiency, and scalability.

Advanced Data Extraction & Transformation

Write, optimize, and debug **complex SQL queries** (including subqueries, CTEs, window functions, and advanced joins) to extract data from various enterprise data warehouses.

Ensure data integrity and consistency between source systems and front-end reports.

Required Technical Skills & Qualifications

Must-Haves (Non-Negotiable)

Power BI & DAX: Minimum of 1–3 years of hands-on experience building Power BI solutions. Deep understanding of evaluation contexts (Filter Context vs. Row Context) and complex DAX functions (CALCULATE, FILTER, ALL, EARLIER, and time-intelligence).

Expert SQL Skills: High proficiency in writing complex, optimized SQL queries. Must be comfortable handling large datasets, writing Common Table Expressions (CTEs), utilizing window functions (RANK, LEAD/LAG, PARTITION BY), and analyzing query performance.

Nice-to-Haves

Data Modeling: Strong understanding of relational database concepts, star/snowflake schemas, and data normalization/denormalization.

Familiarity with cloud data platforms like Snowflake, Azure Synapse, or AWS Redshift.

Basic knowledge of Python for data manipulation.

Soft Skills & Core Competencies

Problem-Solving: A natural curiosity to dig into data anomalies and find the root cause of discrepancies.

Communication: Ability to explain complex technical data constraints to non-technical business users clearly.

Attention to Detail: Precision in data validation to ensure business decisions are made on 100% accurate reporting.

About the Role

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

Key Responsibilities

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

What We're Looking For

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

Tech Stack

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

Perks & Benefits

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

The Data People Shaping Tomorrow

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

Who are we :

Trendlyne is a funded, profitable products startup in the financial markets space. We have cutting-edge analytics products built for Indian and US customers, for stock markets and mutual funds.

Our founders are IIT + IIM graduates, with strong tech and marketing experience. We have top finance and management experts on the Board of Directors.

What do we do :

We build powerful analytics in the US and Indian stock market space that are best-in-class. Organic growth in B2B and B2C products has already made the company profitable. We deliver 1 billion+ APIs every month to B2B customers, and have a B2C website and app.

Experience: 3-6 years | Location: Bangalore (On-site)

Why This Role?

• Real scale, real problems - billions of rows of financial data, millions of API requests per hour, live market feeds.
• Cutting-edge product work - AI products, online backtesting engines, data visualization, and machine learning integrations.
• High ownership, low bureaucracy - small, senior team means your decisions matter and your work ships fast.
• Direct visibility - work closely with founders and product leads on features that reach hundreds of thousands of users.

Tech Stack:

Language: Python

Frameworks: Django / FastAPI / Flask

Databases: PostgreSQL / MySQL

What You'll Do:

• Design, develop, and maintain scalable backend systems capable of handling billions of rows of data and serving millions of API requests per hour
• Translate product requirements into robust system architecture - owning the full development lifecycle from requirement to release
• Collaborate closely with product managers and cross-functional teams to scope and deliver high-quality features that address real user needs
• Write clean, well-documented code and maintain technical documentation that enables other engineers to contribute efficiently
• Drive and participate in design and code reviews, ensuring engineering standards are upheld across the team
• Mentor junior developers, helping build a strong engineering culture within the team
• Contribute to and evolve best practices for backend development as the team and product scale.

What We're Looking For:

• 3-6 years of hands-on experience with Python and at least one of Django / FastAPI / Flask.
• Strong command of relational databases - PostgreSQL or MySQL - and experience optimising queries at scale.
• Solid understanding of Redis and caching strategies in high-throughput environments.
• Experience designing and building REST APIs that are performant, reliable, and maintainable.
• Ownership mindset - you build it, ship it, and take responsibility for it in production.
• Strong communication skills - ability to articulate technical decisions clearly to both engineers and non-technical stakeholders.
• Bonus: Familiarity with JavaScript, HTML, or CSS is a plus but not required.

Role Overview

We are seeking a highly skilled Senior Developer / Technical Lead with strong experience in marketing creative platforms and digital experience delivery. This role requires expertise in Sitecore, React.js, Node.js, Python, and FileMaker, along with proven leadership capabilities to guide development teams and deliver high-impact marketing solutions.

You will play a critical role in designing, developing, and leading the implementation of scalable, creative, and performance-driven digital experiences.

________________________________________

Required Skills & Qualifications

Technical Skills

• Strong experience with:

o Sitecore CMS (content modeling, personalization, pipelines, APIs)

o React.js (modern front-end ecosystem)

o Node.js (RESTful APIs, server-side applications)

o Python (automation, backend systems, scripting)

• Experience with FileMaker (development, customization, or integration)

• Proficiency in HTML5, CSS3, JavaScript/TypeScript

• Experience with API design, microservices architecture, and cloud platforms (AWS )

• Familiarity with CI/CD pipelines, DevOps practices, and version control (Git)

Technical Leadership

• Lead a team of developers, ensuring high-quality design, development, and delivery of solutions

• Provide architectural guidance and enforce best practices across front-end and back-end development

• Mentor junior/mid-level engineers and support team growth

• Ensure scalability, reliability, and security of solutions

Role Overview

We are seeking a highly skilled Operations Research (OR) and Optimization Engineer to design and develop an intelligent crew rostering optimizer for rail operations. The role involves applying advanced optimization techniques—including metaheuristics and mathematical programming—to generate efficient, compliant, and cost-optimized crew schedules. The candidate will also develop production-grade Python code for the optimizer and expose it via APIs for integration with operational systems.

This role combines algorithm design, applied optimization, and production software development.

Key Responsibilities

Optimization Model Design & Development

• Design and implement optimization models for rail crew rostering, considering operational, regulatory, and contractual constraints.
• Apply appropriate optimization techniques such as:
• Mixed Integer Linear Programming (MILP)
• Constraint Programming (CP)
• Metaheuristics (Genetic Algorithm, Simulated Annealing, Tabu Search, Large Neighborhood Search, etc.)
• Hybrid OR + metaheuristic approaches for large-scale optimization
• Model constraints including:
• Duty time limits, rest rules, and labor regulations
• Crew qualifications, route familiarity, and skill requirements
• Shift continuity, fairness, and crew preferences
• Coverage requirements and operational robustness
• Develop objective functions to optimize for cost, utilization, fairness, robustness, and operational efficiency.

Algorithm Engineering & Performance Optimization

• Design scalable and efficient optimization algorithms capable of handling real-world rail network scale.
• Implement solution heuristics and decomposition strategies to improve performance.
• Perform benchmarking, tuning, and performance optimization.

Python Development & API Integration

• Develop modular, production-quality Python code for the optimization engine.
• Expose optimizer functionality via REST APIs (using FastAPI, Flask, or similar frameworks).
• Ensure clean architecture, modular design, and extensibility.
• Package and deploy optimization services for integration with enterprise systems.

Integration & Deployment

• Integrate optimizer with upstream data systems and downstream applications.
• Support deployment in cloud or on-prem environments.
• Ensure robustness, logging, monitoring, and error handling.

Validation & Continuous Improvement

• Validate optimization outputs with domain stakeholders.
• Improve algorithms based on real-world operational feedback.
• Document models, assumptions, and system architecture.

Required Qualifications

Education

• Master's or PhD in one of the following:
• Operations Research
• Industrial Engineering
• Computer Science (with optimization focus)
• Applied Mathematics
• Transportation Engineering
• Artificial Intelligence (with optimization focus)

Technical Skills

Optimization & Algorithms

Strong hands-on experience with:

• Operations Research and optimization modeling
• Metaheuristics such as:
• Genetic Algorithms
• Simulated Annealing
• Tabu Search
• Large Neighborhood Search
• Variable Neighborhood Search
• Mathematical programming techniques:
• MILP, LP, CP

Experience with optimization tools such as:

• OR-Tools
• Pyomo
• PuLP
• Gurobi / CPLEX / CBC
• OptaPlanner (optional)

Impact Analytics™ (Series D Funded) delivers AI-native SaaS solutions and consulting services that help companies maximize profitability and customer satisfaction through deeper data insights and predictive analytics. With a fully integrated, end-to-end platform for planning, forecasting, merchandising, pricing, and promotions, Impact Analytics empowers companies to make smarter decisions based on real-time insights rather than relying on last year’s inputs to forecast and plan this year’s business. Powered by over one million machine learning models, Impact Analytics has been leading AI innovation for a decade, setting new benchmarks in forecasting, planning, and operational excellence across the retail, grocery,

manufacturing, and CPG sectors. In 2025, Impact Analytics is at the forefront of the Agentic AI revolution, delivering autonomous solutions that enable businesses to adapt in real time, optimize operations, and drive profitability without manual intervention.

Here’s a link to our website: www.impactanalytics.co.

Impact Analytics builds AI-powered, Cloud-Native products and platforms. As we tackle increasingly complex backend challenges, we are looking for seasoned backend architects to collaborate with product and engineering teams in shaping the future of enterprise software.

Meet the Team: Rooted in AI and Engineering first principles, our cross-functional teams of ML and AI Engineers and Data Scientist thrive in a fast-paced, innovation-driven environment. We emphasize collaboration, continuous learning, and high-impact delivery. Our backend teams specialize in modern frameworks, data platforms, infrastructure engineering, DevOps practices, and scalable service architectures. Top performers are recognized, valued, and supported with ample growth opportunities.

Role Overview: This is a senior-level, individual contributor role focused on hands-on technical leadership in backend architecture. The role is centered around three core areas:

● Drive complex backend architecture initiatives that span across multiple engineering and technology domains.

● Lead strategic R&D efforts to evaluate new backend technologies, frameworks, and methodologies, and champion their adoption company-wide. ● Spearhead our Multi-Cloud & Hybrid-Cloud backend strategies, ensuring scalable, secure, and resilient architecture patterns.

What our ideal candidate may look like:

● 14+ years of software development experience, with at least 4 years as an Architect or Staff Engineer role, particularly in backend systems.

● A backend technology expert with in-depth, hands-on experience in building and scaling enterprise SaaS with distributed architecture, In depth knowledge of Rest and Event driven architecture with low latency and high-throughput in memory systems.

● Designing stateful backend to handle large data including message broker, distributed queue, caching. Good understanding of High Availability and Disaster recovery for the critical production system.

● In depth understanding of Async, Multi Threading and Multi Processing Architecture to ensure our system efficiently use the programming principle for higher concurrency support

● Proficiency in following programming languages (Python, Rust), with a strong foundation in software engineering principles. Knowledge of Rust is a strong plus, especially in the context of high-performance, memory safety and ownership.

● Deep understanding of system design, database architecture (SQL & NoSQL), microservices, observability, resilience engineering, and secure coding practices.

● Exposure to big data platforms, stream processing, machine learning infrastructure, and multi-cloud environments (e.g., AWS, GCP, Azure) is preferred.

● Excellent communicator and collaborator, with the ability to influence and align cross-functional stakeholders.

● Proven experience mentoring engineers and guiding architectural decisions at scale.

What We Offer

● Opportunity to lead large, high-impact projects for global Fortune 500 clients.

● Work in a high-growth startup environment with a flat, collegial culture.

● Best-in-class remuneration and benefits.

● A platform for personal and professional growth with ownership and autonomy.

Some of our accolades include:

● Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.

● Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.

● Voted #1 by more than 300 retailers worldwide in the RIS Software LeaderBoard 2024 report.

● Ranked #72 in America’s Most Innovative Companies list in 2023—by Fortune—alongside companies like Microsoft, Tesla, Apple, IBM, etc.

● Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.

● Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications.

Interested? Let’s Connect on LinkedIn

About the internship

As a Full Stack Development intern at Miror, you will have the opportunity to work with cutting-edge technologies such as Node.js, React, TypeScript, Python, REST API, Next.js, Claude, ChatGPT, and Prompt Engineering.

Key Responsibilities:

1. Collaborate with the development team to design, build, and maintain efficient, reusable, and reliable code.

2. Implement new features and enhancements on our web application using the latest technologies and best practices.

3. Work on integrating third-party APIs and services to improve the functionality of our platform.

4. Assist in troubleshooting and resolving technical issues to ensure smooth operation of the website.

5. Conduct code reviews and provide constructive feedback to fellow team members.

6. Stay up-to-date with industry trends and advancements in web development to suggest innovative solutions.

7. Contribute to the overall success of the company by actively participating in team meetings and sharing your insights and ideas.

8. AI image and video generation

If you are a passionate and skilled developer looking to gain hands-on experience in a dynamic and fast-paced environment, this internship opportunity is perfect for you.

Join us in revolutionizing the beauty industry with technology!

Skill(s) required

ChatGPT

Claude

Next.js

Node.js

Prompt Engineering

Python

React

REST API

TypeScript

Who can apply

Only those candidates can apply who:

1. are available for full time (in-office) internship

2. can start Immediately

3. are available for duration of 3 months

4. have relevant skills and interests

Other requirements

1. Should be able to independently develop full stack applications

2. Should be open to working directly with business for image and video generation

Perks

Certificate Letter of recommendation

Informal dress code

Chance to get a permanent Job offer here

What We Offer

·       Competitive compensation

·       Opportunity to work with senior leadership

·       Stable role with long-term growth potential

Best Regards,

Indrani Dutta

Senior HR Manager

Soham Renewable Energy India Pvt. Ltd.

Visit: www.miror.in

Visit: https://www.sohamenergy.in/

About Impact Analytics

Impact Analytics is an agentic-first AI software company transforming retail merchandising through cutting-edge AI, LLMs, and Generative AI technologies. As a fast-growing Series D company with deployments across five continents, it is building both industry-leading merchandising solutions and foundational AI agents that are redefining how retail decisions are made. What makes Impact Analytics unique is its combination of deep retail domain expertise, strong innovation culture, and global presence. It is one of the few India-born AI companies recognized globally by organizations like Fortune, Gartner, and the Inc. 5000.For candidates looking to work on next-generation AI products with global scale and real-world impact, Impact Analytics is an exciting place to build your career. Here’s a link to our website: www.impactanalytics.co.

The impact that you will be making

We are seeking a Senior Software Engineer – Backend to design and build scalable backend systems that power Android-first mobile applications. The ideal candidate will have strong backend engineering expertise, experience supporting mobile applications, and a passion for building high-performance, reliable distributed systems that operate efficiently under constrained network conditions.

You will work closely with Android developers and cross-functional teams to build APIs and backend services that enable seamless mobile experiences, including offline synchronization, scalability, and high availability

What lands you in this role

Key Responsibilities

• Design, develop, and maintain scalable backend services and RESTful APIs for Android/mobile applications.
• Build backend systems optimized for Android-first applications with a focus on performance, reliability, and scalability.
• Develop APIs that perform efficiently in low-bandwidth and intermittent network environments.
• Design and implement backend workflows that support offline synchronization, conflict resolution, and data consistency.
• Develop secure, resilient, and highly available microservices.
• Optimize application performance through efficient database design, caching strategies, and API optimization.
• Collaborate closely with Android engineers, Product Managers, QA, and DevOps teams throughout the software development lifecycle.
• Participate in architecture discussions, code reviews, and technical design decisions.
• Leverage AI-assisted development tools to improve engineering productivity and code quality.

Required Skills

• 4–7 years of professional experience in backend software development.
• Strong proficiency in Kotlin for backend development.
• Experience building backend systems supporting Android/mobile applications.
• Strong understanding of RESTful APIs, microservices, and distributed systems.
• Hands-on experience with Gradle (Kotlin DSL/KTS) for build automation and dependency management.
• Familiarity with Android Studio for debugging, API integration, and collaboration with Android teams.
• Experience with modern backend frameworks and scalable application architecture.
• Knowledge of relational and/or NoSQL databases such as PostgreSQL, MySQL, MongoDB, or similar.
• Experience with caching technologies (Redis) and messaging/event streaming platforms (Kafka or RabbitMQ).
• Hands-on experience with Google Cloud Platform (GCP) or equivalent cloud platforms.
• Proficiency with GitHub and modern Git-based development workflows.
• Experience using Visual Studio Code (VS Code).
• Familiarity with AI-powered developer tools such as Cursor, Windsurf, or similar Agentic IDEs.
• Strong understanding of CI/CD pipelines, containerization, and cloud-native application development.
• Excellent debugging, analytical, and problem-solving skills.

What we offer

• An opportunity to be part of some of the best enterprise SaaS products to be built out of India.
• Opportunities to quench your thirst for problem-solving, experimenting, learning, and implementing innovative solutions.
• A flat, collegial work environment, with a work hard, play hard attitude.
• A platform for rapid growth if you are willing to try new things without fear of failure.
• Remuneration with best-in-class industry standards with generous health insurance cover

Some of our accolades include:

• Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.
• Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.
• Voted #1 by more than 300 retailers worldwide in the RIS Software LeaderBoard 2024 report.
• Ranked #72 in America’s Most Innovative Companies list in 2023—by Fortune—alongside companies like Microsoft, Tesla, Apple, IBM, etc.
• Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.
• Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications.

About Impact Analytics

Impact Analytics™ (Series D Funded) delivers AI-native SaaS solutions and consulting services that help companies maximize profitability and customer satisfaction through deeper data insights and predictive analytics. With a fully integrated, end-to-end platform for planning, forecasting, merchandising, pricing, and promotions, Impact Analytics empowers companies to make smarter decisions based on real-time insights rather than relying on last year’s inputs to forecast and plan this year’s business. Powered by over one million machine learning models, Impact Analytics has been leading AI innovation for a decade, setting new benchmarks in forecasting, planning, and operational excellence across the retail, grocery, manufacturing, and CPG sectors. In 2025, Impact Analytics is at the forefront of th eAgentic AI revolution, delivering autonomous solutions that enable businesses to adapt in real time, optimize operations, and drive profitability without manual intervention. Here’s a link to our website: www.impactanalytics.co.

The impact that you will be making

As a senior data scientist, you will help us discover the information hidden in vast amounts of data and help us make smarter decisions to deliver even better products. Primary focus will be in applying data mining techniques, performing statistical analysis, and building high quality prediction systems that can be integrated with our products.

What this role entail

● Understand and translate statistics and analytics to address client business problems.

● Apply Statistical forecasting algorithms to forecast client business needs for short term and long-term horizon.

● Explore Machine learning and Deep learning techniques to improve statistical Forecasting accuracy.

● Create business narrative by using storytelling and Visualization techniques and to present analytical insights to clients.

● Structure business problems and design solutions to meet client needs.

● Develop sophisticated analytical frameworks that add value to the client and result in new projects and revenue streams.

● Develop and implement analytical methodologies, processes, and technological solutions that integrate diverse information solutions and generate analytical insights.

What lands you in this role

● At least 3 years hands-on experience as a data scientist working on SQL, Python

● Must have exposure to developing predictive analytics and machine learning algorithms for business applications

● Strong forecasting and Deep Learning experience will be a plus

● Hands-on experience in relevant tools like SQL, Python, Tableau, etc.

● B Tech/ BE or equivalent degree in Data Science, Statistics, Computer Science, or similar

Some of our accolades include:

● Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.

● Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.

● Voted #1 by more than 300 retailers worldwide in the RIS Software Leaderboard 2024 report.

● Ranked #72 in America’s Most Innovative Companies list in 2023—by Fortune—alongside companies like Microsoft, Tesla, Apple, IBM, etc.

● Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.

● Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications. Economic Times News about our funding can be accessed here.

Position: Site Reliability Engineer (SRE)

Location: Bangalore / Trichy

Experience: 4–6 Years

No of Open Positions: 2

We Need Immediate Joiners

We are hiring a hands-on Site Reliability Engineer (SRE) to support Kubernetes-based production platforms, automation, and cloud operations.

Mandatory (Non-Negotiable)

• Active CKA (Certified Kubernetes Administrator) certification – mandatory
• Strong hands-on Kubernetes Administration experience
• Linux Administration
• Scripting in Bash / Python / Terraform / GoLang
• Experience supporting production environments and troubleshooting infrastructure issues
• 4–6 years of experience
• Bangalore / Trichy location or willing to relocate
• 
  

Good to Have

• AWS Cloud exposure
• CI/CD & DevOps practices
• Monitoring, logging & observability tools
• Infrastructure as Code (IaC)

Key Responsibilities

• Administer, upgrade, scale, and troubleshoot Kubernetes clusters
• Automate operational tasks and infrastructure provisioning
• Support CI/CD pipelines and platform reliability initiatives
• Handle production incidents, RCA, and preventive actions

WHO WE ARE:

TIFIN is a fintech platform backed by industry leaders including JP Morgan, Morningstar, Broadridge, Hamilton Lane, Franklin Templeton, Motive Partners and a who’s who of the financial service industry. We are creating engaging wealth experiences to better financial lives through AI and investment intelligence powered personalization. We are working to change the world of wealth in ways that personalization has changed the world of movies, music and more but with the added responsibility of delivering better wealth outcomes.

We use design and behavioral thinking to enable engaging experiences through software and application programming interfaces (APIs). We use investment science and intelligence to build algorithmic engines inside the software and APIs to enable better investor outcomes.

In a world where every individual is unique, we match them to financial advice and investments with a recognition of their distinct needs and goals across our investment marketplace and our advice and planning divisions.

OUR VALUES: Go with your GUT

• Grow at the Edge. We are driven by personal growth. We get out of our comfort zone and keep egos aside to find our genius zones. With self-awareness and integrity we strive to be the best we can possibly be. No excuses.
• Understanding through Listening and Speaking the Truth. We value transparency. We communicate with radical candor, authenticity and precision to create a shared understanding. We challenge, but once a decision is made, commit fully.
• I Win for Teamwin. We believe in staying within our genius zones to succeed and we take full ownership of our work. We inspire each other with our energy and attitude. We fly in formation to win together.

Responsibilities:

• Develop user-facing features such as web apps and landing portals.
• Ensure the feasibility of UI/UX designs and implement them technically.
• Create reusable code and libraries for future use.
• Optimize applications for speed and scalability.
• Contribute to the entire implementation process, including defining improvements based on business needs and architectural enhancements.
• Promote coding, testing, and deployment of best practices through research and demonstration.
• Review frameworks and design principles for suitability in the project context.
• Demonstrate the ability to identify opportunities, lay out rational plans, and see them through to completion.

Requirements:

• Bachelor’s degree in Engineering with 10+ years of software product development experience.
• Proficiency in React, Django, Pandas, GitHub, AWS, and JavaScript, Python
• Strong knowledge of PostgreSQL, MongoDB, and designing REST APIs.
• Experience with scalable interactive web applications.
• Understanding of software design constructs and implementation.
• Familiarity with ORM libraries and Test-Driven Development.
• Exposure to the Finance domain is preferred.
• Knowledge of HTML5, LESS/CSS3, jQuery, and Bootstrap.
• Expertise in JavaScript fundamentals and front-end/back-end technologies.

Nice to Have:

• Strong knowledge of website security and common vulnerabilities.
• Exposure to financial capital markets and instruments.

Compensation and Benefits Package:

• Competitive compensation with a discretionary annual bonus.
• Performance-linked variable compensation.
• Medical insurance.

A note on location. While we have team centers in Boulder, New York City, San Francisco, Charlotte, and Mumbai, this role is based out of Bangalore

TIFIN is an equal-opportunity workplace, and we value diversity in our workforce. All qualified applicants will receive consideration for employment without regard to any discrimination.

Looking for somone with strong in AI, who have built the application and scaled them . Start up work exposure

8+ years of experience in successfully building, deploying, and running complex, large-scale web or data products.

Proven Management Experience: Demonstrated success managing a team of 5+ engineers for at least 2 years (managing timelines, performance, and hiring). You know how to transition a team from 'startup chaos' to 'structured agility'. 

● Full-stack Authority: Deep expertise with Javascript, Node.js, MySQL, and Python. You must have world-class expertise in at least one area but possess a solid understanding of the entire stack in a multi-tier environment. 

● Architectural Track Record: Has built at least two professional-grade products as the tech owner/architect and led the delivery of complex products from conception to release. 

● Experience in working with REST APIs, Machine Learning, Algorithms & AWS. 

● Familiar with visualization libraries and database technologies.

 ● Your reputation in the technology community within your domain. 

● Your participation and success in competitive programming. 

● Work on unusual/extraordinary hobby projects during school/college that were not a part of the curriculum. 

● The school that you come from and organizations where you have worked earlier. Personality Expectations We believe that it takes a certain type of personality to do a certain kind of role well. 

● Thoughtful & Analytical: Unlike a sales role, this role requires deep analytical ability and thoughtfulness. You don't just "hit goals at any cost"; you architect sustainable solutions that prevent future debt. 

● The "Pack Leader" Mentality: You are competitive, but you understand that your team's win is your win. You shift from getting a dopamine hit from solving a bug yourself to getting a hit from unblocking your team to solve ten bugs. 

● High Ownership of Outcomes: You don't just care that the code was written; you care that the feature was delivered, works for the customer, and didn't break production. You expect very highly of yourself and being less than ideal anywhere almost pains you. 

● Resilience: You possess the mental endurance to push through complex technical constraints and tight deadlines without losing your cool. 

● Uncompromising Values: On the other side, there is only one thing that we care for apart from performance - your values. We have room for mistakes on the performance side, we have no room for mistakes on your values. 

Job Summary

We are seeking a motivated Data Engineer with strong skills in SQL, Python, and Linux to design, build, and maintain scalable data pipelines and support data-driven decision-making. The ideal candidate should have experience working with large datasets, ETL processes, and relational databases while ensuring data quality and performance.

Key Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines.
• Write optimized SQL queries, stored procedures, and database objects.
• Develop Python scripts for data extraction, transformation, and automation.
• Work in Linux environments to manage scripts, cron jobs, and system processes.
• Monitor and troubleshoot data pipeline failures.
• Ensure data integrity, consistency, and quality across systems.
• Collaborate with data analysts, software engineers, and business stakeholders.
• Optimize database performance and query execution.
• Participate in code reviews and follow best engineering practices.

Required Skills

• Strong proficiency in SQL (joins, subqueries, window functions, CTEs, indexing, query optimization).
• Good programming experience in Python.
• Hands-on experience with Linux commands and shell scripting.
• Understanding of ETL/ELT concepts and data warehousing.
• Knowledge of relational databases such as PostgreSQL, MySQL, Oracle, or SQL Server.
• Familiarity with Git for version control.
• Strong problem-solving and analytical skills.

Job Summary

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.

Key Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines.
• Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
• Develop automation scripts using Python for data processing and workflow optimization.
• Work with Linux environments for deployment, monitoring, and troubleshooting.
• Ensure data quality, integrity, and reliability across data platforms.
• Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
• Implement best practices for data security, governance, and documentation.

Required Skills

• Strong experience in Data Engineering concepts and ETL/ELT processes.
• Proficiency in SQL, including query optimization and database design.
• Strong programming skills in Python.
• Hands-on experience with Linux commands, shell scripting, and system administration basics.
• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Familiarity with Git/version control.
• Strong analytical and problem-solving skills.

Preferred Skills

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
• Experience with data warehousing solutions and big data technologies.
• Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Relevant certifications in cloud or data engineering are an added advantage.

AI/ML Engineer AI Operating System for Capital Markets Location Bangalore/Chennai Experience 5+ years Function Artificial Intelligence / Machine Learning Employment Type About Transient.AI Full-time Transient.AI is building a next-generation AI Operating System for capital markets — a unified intelligence layer that connects research, trading, compliance, and sales functions at banks and hedge funds. Today, these teams largely operate on disconnected legacy systems, forcing manual, expensive workarounds. Transient.AI replaces that fragmentation with a single AI-native layer built for institutional-grade compliance, security, and auditability. The company already has live products in market, including Caddie.AI (a research automation tool that cuts hedge fund research time significantly), ClarityRIA (helping sales teams identify the right investors in seconds), and CapFlo.AI (automated parsing of complex derivatives contracts). Founded by former traders and technologists from Goldman Sachs, Credit Suisse, UBS, and McKinsey, Transient.AI is headquartered in New York, with teams in Miami, Singapore, and India. The company has raised Series A funding and is scaling its engineering and product organization globally. Role Overview Transient.AI is hiring an experienced AI/ML Engineer to join its India engineering team in Bangalore/Chennai. This is a hands-on, build-from-scratch role — you'll be designing and shipping the core machine learning systems that power the company's flagship products, working closely with founders and senior engineers rather than inheriting existing infrastructure. Key Responsibilities • Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research automation, document intelligence, investor matching, and workflow orchestration). • Workonapplied NLP/LLMsystems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines. • Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems. • Ownmodelperformance, reliability, and cost — from experimentation through production deployment. • Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration. • Ensuresystems meet the compliance, auditability, and security standards required in regulated financial environments. What We're Looking For • 5+years ofexperience building and deploying machine learning or AI systems in production.• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent). • Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly valued. • Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning). • Prior experience at a strong product company, high-growth startup, or a top-tier engineering background • Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity. • Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory. WhyJoin Transient.AI • Build core AI systems from the ground up — not maintain legacy code. • Workdirectly with founders who have deep, first-hand Wall Street experience (Goldman Sachs, Credit Suisse, UBS, McKinsey). • JoinaSeries A-funded company solving a real, expensive problem for institutional finance. • Bepart ofasmall, global team with outsized ownership and impact. .

Job Summary

We are looking for an experienced AI Data Architect to design and build an enterprise AI-ready data platform that serves as the single source of truth for AI applications, including RAG, Agentic AI, Conversational AI, ML models, and analytics.

Key Responsibilities

• Design enterprise AI data platform and Lakehouse architecture.
• Build batch & real-time data pipelines.
• Develop semantic models, knowledge graphs, and vector databases.
• Architect RAG and LLMOps infrastructure.
• Implement data governance, security, and AI observability.
• Modernize legacy data platforms to cloud-native architectures.

Required Skills

• Python, SQL, PySpark
• Databricks, Delta Lake, Snowflake
• Kafka, Spark Structured Streaming
• AWS / Azure
• LangChain, LlamaIndex
• OpenAI, Claude, Bedrock
• Pinecone, FAISS, ChromaDB, Neo4j
• MLflow, Docker, Kubernetes, Terraform
• FastAPI, GitHub Actions, Jenkins
• Data Governance, RBAC, CI/CD

Requirements

• 12+ years in Data Engineering/Data Architecture.
• Experience with AI/ML, RAG, LLMOps, and enterprise AI platforms.
• Strong expertise in Lakehouse, Data Mesh, Cloud, and Vector Databases.
• Hands-on experience with enterprise-scale AI data architecture and governance. 

About the Role

We're looking for a Senior AI/ML Engineer who thrives at the intersection of research and production — someone who doesn't just build models, but ships systems that scale. You'll own the full ML lifecycle: architecting robust data pipelines, training and rigorously evaluating models, and deploying them into high-throughput production environments. This is a role for engineers who want their work to move fast, break assumptions (not systems), and directly shape how AI gets built at scale. If you're energized by turning cutting-edge research into real-world impact, this is your next challenge.

Key Responsibilities

– Design, build, and maintain end-to-end ML pipelines — from raw data ingestion to model serving — with a focus on scalability and reliability.

– Develop, train, and rigorously evaluate ML/DL models using sound experimentation practices (A/B testing, offline/online metrics, statistical validation).

– Own the MLOps lifecycle: implement CI/CD pipelines for model training and deployment, version control for datasets and models, and automated retraining workflows.

– Deploy and monitor models in production using containerized, orchestrated infrastructure (Docker, Kubernetes), ensuring low-latency, high-availability inference.

– Collaborate cross-functionally with Data Engineering, Product, and Backend teams to translate business problems into scalable ML solutions.

– Optimize model performance for cost, latency, and accuracy trade-offs across cloud-based training and inference environments.

– Mentor and guide junior engineers and data scientists — conducting code reviews, sharing best practices, and raising the technical bar of the team.

– Stay current with emerging research (LLMs, generative AI, RAG architectures) and proactively identify opportunities to apply them to existing products.

Required Technical Skills

Languages

– Expert-level Python; working knowledge of R or C++ is a plus.

Frameworks

– TensorFlow, PyTorch, Scikit-Learn, Keras.

Data & Cloud

– Strong SQL and NoSQL fundamentals.

– Hands-on experience with at least one major cloud platform (AWS, GCP, or Azure), specifically their ML tooling — SageMaker, Vertex AI, or equivalent.

– Experience with distributed data processing frameworks: Spark, Hadoop.

MLOps & Deployment

– Proficiency with Docker and Kubernetes for containerized deployment.

– Experience building CI/CD pipelines for ML workflows.

– Familiarity with experiment tracking and pipeline orchestration tools like MLflow or Kubeflow.

Advanced / Nice-to-Have

– Practical experience with LLMs, prompt engineering, and Retrieval-Augmented Generation (RAG) architectures.

– Experience fine-tuning transformer-based models for domain-specific use cases.

Qualifications & Experience

– Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.

– 5+ years of hands-on experience building, training, and deploying production-grade AI/ML models at scale.

– Demonstrated track record of taking models from prototype to production in a real-world business setting.

What We Offer

– Competitive compensation, benchmarked to top-tier tech talent in the industry.

– Comprehensive health insurance coverage for you and your family.

– Annual learning & development stipend for courses, certifications, and conferences.

– A collaborative, high-ownership culture where engineering excellence is celebrated.

– The opportunity to work on cutting-edge AI systems with direct, visible impact.

About Tech Transient

Tech Transient is an AI consulting and digital transformation firm headquartered in Coimbatore, Tamil Nadu.

We partner with enterprises and growth-stage companies to design and deliver intelligent digital products — spanning mobile applications, cloud platforms, and AI-driven solutions. Our mission is to translate emerging technology into measurable business outcomes.

Machine Learning Engineer (For client company)

Location: Bengaluru, India (Hybrid/Onsite)

Experience: 3–4 years

The Role

We are looking for a Machine Learning Engineer to build and productionize models that power fall detection, vitals monitoring, and predictive health insights from radar sensor data.

You will work closely with hardware, data engineering, backend, and product teams to improve model accuracy, reduce false alarms, and deploy reliable ML systems into production.

This role is ideal for someone with strong classical machine learning fundamentals who is comfortable working with messy real-world sensor data and writing clean, production-grade code.

What You'll Do

• Build and optimize classical ML models such as XGBoost, ensemble models, anomaly detection, and time-series models for fall detection, vitals monitoring, and health risk scoring.
• Engineer features from raw, sparse, and noisy radar signals, point-cloud data, and time-series sensor streams.
• Contribute to computer vision-adjacent problems such as pose estimation, movement analysis, skeleton tracking, and activity recognition using radar data.
• Build training, evaluation, and inference pipelines using Databricks.
• Perform exploratory data analysis on resident, device, alert, and facility-level datasets to identify trends, edge cases, and opportunities for model improvement.
• Define and own model evaluation metrics for safety-critical systems, including:
• Precision
• Recall
• Sensitivity
• Specificity
• False alarm rate
• Missed event rate
• Detection latency
• Analyze production model performance across facilities, residents, devices, and time periods.
• Handle noisy real-world datasets, including:
• Missing values
• Label quality issues
• Device variability
• Sparse event data
• Facility-specific patterns
• Write clean, modular, well-tested Python code for feature engineering, model training, evaluation, and inference.
• Deploy, monitor, and continuously improve production ML models.
• Collaborate with hardware and data engineering teams to improve data quality, labeling, observability, and model reliability.

What We're Looking For

• 3–4 years of experience building and deploying machine learning systems in production.
• Strong Python programming skills with the ability to write maintainable, testable, production-grade code.
• Strong understanding of classical machine learning concepts, including:
• Feature engineering
• Model training
• Cross-validation
• Error analysis
• Model evaluation
• Hands-on experience with algorithms such as:
• XGBoost
• Random Forests
• Gradient Boosting
• Ensemble methods
• Anomaly Detection
• Time-series models
• Strong SQL skills with experience analyzing large datasets using SQL, PySpark, Pandas, or Databricks.
• Experience working with time-series, sensor, spatial, point-cloud, IoT, or computer vision-style datasets.
• Familiarity with modern data engineering workflows using Databricks, Apache Spark, Delta Lake, or similar platforms.
• Strong debugging and analytical skills with the ability to diagnose issues across data pipelines, models, and production systems.
• Comfortable working in a fast-moving startup environment with ambiguity.
• Strong ownership mindset with the ability to take ML models from experimentation through production deployment.

Good to Have

• Experience in HealthTech, IoT, radar sensing, wearables, ambient monitoring, or safety-critical systems.

Exposure to:

• Computer Vision
• Pose Estimation
• Skeleton Tracking
• Object Tracking
• Spatial Data Processing
• Experience with:
• MLflow
• Model Registry
• Feature Stores
• Experiment Tracking
• Model Monitoring
• Experience with:
• ONNX
• Model Quantization
• Edge Deployment
• Latency Optimization
• Resource-Constrained Inference
• Familiarity with real-time data pipelines using:
• Kafka
• Spark Structured Streaming
• Streaming inference architectures 

5 -10 years of professional software development experience.

 Experience in any backend tech like Java/Golang/Python/Nodejs/Ruby and Frontend Tech like Reactjs/Angular/Vuejs

with strong working knowledge of frontend/backend frameworks.

 Strong understanding of software architecture, design patterns, and principles

(e.g., SOLID, microservices, event-driven architectures)

 Experience with AI tools, frameworks, platforms, and their application in software delivery

 Experience with cloud platforms (especially AWS services), containerization and orchestration (Docker, Kubernetes)

 Hands-on experience with CI/CD pipelines and automated testing frameworks

 Familiarity with databases (SQL and NoSQL) and data modelling

 Fluency with XP practices: TDD, pair programming, continuous integration,

refactoring

 Working knowledge of security principles (secrets management, least privilege)

Job Summary:

We are seeking a highly skilled Principal Infrastructure Engineer to join our team, focusing on production support and Site Reliability Engineering (SRE) implementation. The ideal candidate will possess a strong background in Python scripting, Ansible automation, and OpenShift support, along with expertise in Linux administration and Apache Tomcat. This role is critical in ensuring the stability and performance of our applications through effective monitoring, log analysis, and the use of various DevOps tools.

Responsibilities:

Provide production support for applications, ensuring high availability and performance.

Implement Site Reliability Engineering (SRE) practices to enhance system reliability.

Develop and maintain Python scripts for automation and process improvement.

Utilize Ansible for configuration management and deployment automation.

Support and manage OpenShift environments, ensuring optimal performance and scalability.

Administer Linux servers, ensuring security, performance, and reliability.

Manage and configure Apache Tomcat servers for application deployment.

Implement and maintain monitoring tools to proactively identify and resolve issues.

Conduct log analysis to troubleshoot and optimize application performance.

Collaborate with cross-functional teams to enhance DevOps practices and tools.

Document processes, procedures, and best practices for infrastructure management.

Mandatory Skills:

Strong experience in application production support.

Proficiency in Python scripting for automation tasks.

Hands-on experience with Ansible for automation and orchestration.

Solid understanding of OpenShift and container orchestration.

Expertise in Linux administration, including server setup and maintenance.

Experience with Apache Tomcat configuration and management.

Familiarity with monitoring tools and log analysis techniques.

Knowledge of DevOps tools and practices.

Preferred Skills:

Experience with cloud platforms (AWS, Azure, GCP).

Familiarity with CI/CD pipelines and tools.

Knowledge of networking concepts and security best practices.

Experience with database management and optimization.

Understanding of Agile methodologies and practices.

Qualifications:

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

Relevant certifications in cloud technologies, DevOps, or system administration are a plus.

Strong analytical and problem-solving skills.

Excellent communication and collaboration abilities.

Ability to work in a fast-paced environment and manage multiple priorities

Key Responsibilities:

·       Design, develop, and maintain scalable data warehouse solutions using Snowflake.

·       Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.

·       Develop and support ETL processes using Talend to ensure reliable and efficient data movement.

·       Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.

·       Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.

·       Debug and troubleshoot Python-based data processing scripts and automation workflows.

·       Implement best practices for data quality, testing, deployment, and code reviews.

·       Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.

·       Monitor, optimize, and maintain data warehouse performance and operational stability.

·       Create and maintain technical documentation, data models, and process workflows.

Required Skills and Experience: 

·       Strong hands-on expertise in Snowflake Data Warehouse.

·       Advanced SQL skills with experience handling large-scale datasets.

·       Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.

·       Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.

·       Experience developing and maintaining ETL solutions using Talend.

·       Proficiency in Python for scripting, debugging, automation, and data processing.

·       Experience integrating UI, API, and Data Warehouse workflows.

·       Strong problem-solving and analytical skills.

·       Experience with testing, code reviews, and deployment best practices.

·       Excellent communication and stakeholder management skills.

Job Summary

We are seeking a highly skilled and experienced Senior Salesforce QA Engineer to lead the end-to-end quality assurance for our enterprise Salesforce platform. In this role, you will design robust test strategies, establish automated testing pipelines, and validate complex custom configurations, Apex code, and integrations. As a senior member of the team, you will bridge the gap between business requirements and technical execution, ensuring the delivery of high-quality, scalable solutions across Sales, Service, and Custom Clouds.

Key Responsibilities

• Test Strategy & Planning: Define, implement, and maintain comprehensive test strategies, test plans, and test cases covering functional, regression, integration, and end-to-end scenarios.

• Test Automation: Architect, scale, and maintain automated testing frameworks using enterprise tools (e.g., Provar, Tricentis Tosca, or Selenium with Java/Python) specifically optimized for Salesforce's dynamic UI.

• Complex Custom Validation: Validate complex programmatic customizations (Apex classes, Triggers, Lightning Web Components) and declarative features (Advanced Flows, Validation Rules).

• Integration Testing: Lead end-to-end API testing (REST/SOAP) to verify seamless data flow between Salesforce and upstream/downstream external systems.

• Environment & Release Management: Oversee sandbox deployments, data masking, and regression testing during Salesforce seasonal releases and monthly deployment cycles.

• Defect Lifecycle Management: Own the defect tracking process in Jira or Azure DevOps, collaborating closely with developers, business analysts, and product owners for rapid root-cause resolution.

• Mentorship & Leadership: Provide technical guidance and mentorship to junior QA engineers and lead user acceptance testing (UAT) phases with business stakeholders.

Required Technical Skills & Qualifications

• Experience: 5 to 10 years of dedicated software quality engineering experience, with a minimum of 3+ years focused exclusively on testing Salesforce ecosystems.

• Salesforce Core Knowledge: Deep understanding of Salesforce architecture, data models, object relationships, sharing rules, and platform governor limits.

• Automation Expertise: Hands-on experience developing framework code or no-code architectures using tools like Provar, Selenium WebDriver, Tricentis Tosca, or UFT.

• API Testing: Proficient in API testing tools such as Postman, SoapUI, or automated API frameworks.

• Agile & Devops: Strong experience working within Agile/Scrum methodologies and integrating automated tests into CI/CD pipelines (e.g., Copado, Jenkins, GitHubActions).

• Data Management: Proficiency in writing SQL queries and utilizing Salesforce Data Loader for test data creation and verification.

We are seeking a Technology Solutions Engineer with 3–5 years of hands-on software development experience who is passionate about exploring new technologies and solving business problems through rapid prototyping. The role focuses on evaluating technology solutions, building proof-of-concept (POC) applications, validating third-party integrations, and assessing the technical feasibility of business requirements before production implementation.

Responsibilities:

• Understand business requirements and convert them into technical solution options.
• Research, evaluate, and compare SaaS products, AI platforms, cloud services, and enterprise applications.
• Develop POCs and prototypes to validate technical feasibility.
• Build and test integrations using REST APIs, webhooks, SDKs, and authentication mechanisms.
• Perform technical, scalability, security, and cost feasibility assessments.
• Prepare solution comparison reports, architecture diagrams, and technical recommendations.
• Collaborate with business users, vendors, and engineering teams during evaluations.
• Identify technical risks, assumptions, and implementation dependencies.
• Support engineering teams in transitioning successful POCs into production.
• Maintain clear technical documentation.

Criteria:

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

·      3–5 years of hands-on experience in software development, integration engineering, or solution engineering.

·      Strong coding skills in Python, Node.js, Java, or C#.

·      Experience working with REST APIs, JSON, OAuth, webhooks, and API testing tools.

·      Hands-on exposure to AWS or another major cloud platform.

·      Experience with Git, Docker, and SQL databases.

·      Excellent analytical, troubleshooting, and communication skills

·      Comfortable collaborating across product, engineering, and business teams

·      Excellent communication, problem-solving, and stakeholder management skills.

Preferred Skills

• Exposure to OpenAI, Gemini, Claude, or other AI/LLM platforms.
• Experience evaluating third-party enterprise software.
• Basic knowledge of Kubernetes, Terraform, CI/CD, Redis, or Kafka.
• Ability to create architecture diagrams and technical proposals.

What Makes You Successful

• Quickly builds functional POCs to validate ideas.
• Can independently evaluate multiple technical approaches.
• Balances technical quality, implementation effort, and business value.
• Communicates findings clearly to technical and non-technical stakeholders.

Company Name – Wissen Technology

Group of companies in India – Wissen Technology & Wissen Infotech

Work Location – Whitefield, Bangalore

While you may already know about Wissen and the company history, here is a quick rundown for you.

About Wissen Technology:

·    The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015.

·    Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains. We help clients build world class products.

·    Our workforce has highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like Wharton, MIT, IITs, IIMs, and NITs and with rich work experience in some of the biggest companies in the world.

·    Wissen Technology has grown its revenues by 400% in these five years without any external funding or investments.

·    Globally present with offices US, India, UK, Australia, Mexico, and Canada.

·    We offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.

·    Wissen Technology has been certified as a Great Place to Work®.

·    Wissen Technology has been voted as the Top 20 AI/ML vendor by CIO Insider in 2020.

·    Over the years, Wissen Group has successfully delivered $650 million worth of projects for more than 20 of the Fortune 500 companies.

·    We have served client across sectors like Banking, Telecom, Healthcare, Manufacturing, and Energy. They include likes of Morgan Stanley, Goldman Sachs, MSCI, StateStreet, Flipkart, Swiggy, Trafigura, GE to name a few.

Job Title: Azure Fabric Data Engineer / AI Engineer

Experience: 4–8 Years

Location: Pune(Hybrid)

Job Summary

We are seeking Azure Fabric Data Engineers with experience in data engineering, Power BI, and AI to build modern data platforms and AI-driven solutions on Microsoft Fabric.

Key Responsibilities

• Develop ETL/ELT pipelines using Microsoft Fabric.
• Integrate data from multiple enterprise systems into Fabric.
• Build and optimize Lakehouse and Data Warehouse solutions.
• Develop Power BI dashboards and reports.
• Build AI-powered applications, AI Agents, and chatbots using Azure AI Services and Azure OpenAI.
• Collaborate with business and technical teams to deliver scalable analytics solutions.

Required Skills

• Microsoft Fabric
• Data Engineering and ETL/ELT
• SQL, Python, PySpark
• Power BI
• Azure AI Services / Azure OpenAI
• Data Modeling
• Git and Azure DevOps

Preferred: Experience with Financial Services/Capital Markets, Generative AI, RAG, or LLM-based applications.

Senior Gen AI Full Stack Engineer:

• Strong background in AI/ML and Gen AI with a deep understanding of LLMs, NLP pipelines, and AI model lifecycle.

• Experience in designing and building guardrail systems for Gen AI applications – including prompt filtering, semantic validation, toxicity detection, and hallucination mitigation.

• Fast API experience for API development.

• Proficiency in Python with frameworks like LangChain, Transformers, OpenAI, and LLM orchestration tools.

• Strong DevOps skills including CI/CD, Docker, Kubernetes, and Git.

Experience integrating Gen AI models into enterprise platforms securely and ethically.

On the Job

● Build and maintain scalable cloud infrastructure on AWS

● Improve CI/CD pipelines, deployment systems, and developer workflows

● Automate infrastructure provisioning using Infrastructure-as-Code (Terraform/Pulumi)

● Manage and optimize Kubernetes clusters and containerized workloads

● Improve observability across systems through monitoring, logging, and alerting

● Drive reliability initiatives including incident response, root cause analysis, and operational

improvements

● Collaborate with engineering teams to improve service scalability, performance, and security

● Implement IAM, secrets management, and infrastructure security best practices

● Optimize infrastructure costs and improve resource efficiency

● Actively leverage AI tools and workflows to improve engineering productivity and automation

Must Haves

● 3–6 years of experience in DevOps, Platform Engineering, or SRE roles

● Strong hands-on experience with AWS infrastructure and services

● Good understanding of Kubernetes, Docker, and container orchestration

● Experience with Infrastructure-as-Code tools like Terraform or Pulumi

● Strong scripting/coding skills in Python, Go, or Bash

● Experience building and maintaining CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI,

etc.)

● Understanding of networking fundamentals, Linux systems, and cloud security practices

● Familiarity with monitoring and observability tools like Prometheus, Grafana, ELK, Datadog,

etc.

● Strong debugging and problem-solving skills

● Ability to work independently in a fast-moving environment

Good To Haves

● Experience working in fintech or high-scale startup environments

● Exposure to service mesh, zero-trust security, or secrets management systems

● Experience with multi-cluster Kubernetes environments

● Familiarity with incident management, SLOs, and reliability engineering practices

● Experience building internal developer platforms or automation tooling

Hiring for Lead Python Developer

Exp : 7+ yrs

Edu : BE/B.Tech

Work Location : Bengaluru / Gurugram Hybrid

Skills :

Strong expertise in Python programming. 

Experience with frameworks such as: Django Flask FastAPI 

Strong understanding of: REST APIs Microservices Architecture OOPs Concepts Design Patterns 

Experience with databases: PostgreSQL MySQL MongoDB Redis 

Hands-on experience with: Docker Kubernetes CI/CD Pipelines Git/GitHub/GitLab 

Cloud platform experience: AWS / Azure / GCP 

Knowledge of message brokers: Kafka / RabbitMQ 

Experience with unit testing and automation frameworks. 

Leadership Skills Strong team handling and mentoring experience. 

Ability to drive technical discussions and architecture decisions. 

Excellent stakeholder management and communication skills. 

Experience managing Agile/Scrum teams. 

Preferred Qualifications Bachelor’s/Master’s degree in Computer Science or related field.

 Experience in large-scale enterprise applications.

Exposure to AI/ML integrations is an added advantage. Certifications in cloud or Python technologies are preferred.

Role overview:

We are hiring one Senior Backend Engineer to take end-to-end ownership of our serverless backend — a hands-on IC role for someone both technically excellent and comfortable being one of the few people the entire backend depends on. You'll own the services across several Node.js and Python repositories, work directly with the founders and product team, and set the technical bar for reliability, security, and performance.

Key responsibilities

• Design, build, and operate AWS Lambda services across our HCM/workforce, project-management, commercial/revenue, permissions, and document domains — each comprising dozens of functions.
• Own the multi-tenant PostgreSQL data layer — schema design, query performance, and the permission/relationship model — end to end.
• Maintain and evolve the request path — API Gateway → custom Lambda authorizer → VPC-bound Lambda → private databases — including the runtime IAM/credential model that scopes every request.
• Safeguard tenant isolation and security across a per-company Cognito authentication model.
• Build and maintain integrations with external construction data environments (Asite, Autodesk Construction Cloud), including large-scale document synchronization.
• Optimize performance and reliability to keep latency-sensitive endpoints well within platform limits under growing load.
• Raise the engineering bar — testing, observability, CI/CD, and modernization of legacy components.
• Debug and resolve production incidents to root cause, and put safeguards in place so they don't recur.
• Document decisions and designs and collaborate with the frontend (Angular) and product teams.

Challenges you'll solve.

We prefer to be candid — these are the problems that make this role genuinely interesting:

Latency under a hard ceiling

API Gateway terminates any request beyond ~29 seconds regardless of the Lambda's own timeout — yet much of our value comes from heavy cross-project reporting. You'll keep p95 latency within budget through set-based SQL, pagination, streaming, and asynchronous processing.

Least-privilege, per-request security

A shared custom authorizer mints short-lived, request-scoped credentials via sts:AssumeRole under a strict 2,048-character inline session-policy limit. You'll design permission models that stay within that budget and reason about IAM precisely.

Graph-shaped data, relational store

The permission and relationship model is inherently graph-like, but lives in PostgreSQL — you'll model it with recursive queries, careful indexing, and set-based traversal rather than reaching for a separate graph engine.

Watertight multi-tenancy

One Cognito pool per company and tenant-scoped access throughout — isolation is a first-order concern.

VPC-bound serverless

Lambdas run inside a VPC to reach private databases; you'll manage cold starts, connection lifecycles, and pool limits.

Resilient external integrations

Syncing large document sets from third-party APIs (including SOAP/XML) demands backpressure, deduplication, retries, and graceful partial-failure handling.

Compute-heavy workloads

Server-side PDF generation, image processing, and multi-currency handling within Lambda's memory and time constraints.

The stack.

Runtime — Node.js, Python, AWS Lambda

AWS services — -1 API Gateway, Lambda, Cognito, STS / IAM, Secrets Manager, S3 CloudWatch, VPC, EC2

Infrastructure & CI/CD- AWS SAM, CodePipeline → CodeBuild Shared Data —PostgreSQL

Qualifications.

• 5+ years building and operating production backend systems.
• Deep expertise in Node.js and JavaScript — the asynchronous model, event loop, and memory behavior — plus solid working proficiency in Python and its production behavior.
• Strong hands-on AWS experience, ideally serverless (Lambda, API Gateway, IAM/STS, VPC, Secrets Manager, CloudWatch) — able to reason about IAM policies, not just apply them.
• Advanced SQL and relational data modeling — set-based query design and a working understanding of why N+1 patterns cause production issues.
• Proven production-debugging ability — root-cause analysis in distributed systems from logs and first principles.
• Strong ownership, sound judgment, and clear written communication — able to make good decisions with incomplete information and explain trade-offs to non-engineers.

Interview Process:

Introductory call-Mutual fit and role overview.

Technical deep-dive- A walkthrough of a challenging production problem you have owned.

Practical exercise -A realistic backend task, or a walkthrough of your own representative code.

System design- Collaborative design on a real scenario.

Final conversation- Values, ownership, compensation, and offer.

Job Title: Principal Automation Engineer (AI)

Deltek is seeking a Principal Automation Engineer with deep expertise in AI-native test automation to help shape the quality engineering foundation Deltek’s next-generation, AI-first ERP platform for project-based businesses. This is not a role for someone who automates feature regression. It is a role for someone who can harness AI tools to build intelligent automation frameworks that reason, adapt, and self-heal.

You will be the automation architect behind Deltek’s in-house AI-native test automation platform combining Playwright with LLM-powered agents (Planner, Generator, Healer). You will extend, evolve, and industrialize this framework, integrating AI tools at every layer: test generation, self-healing selectors, LLM-as-a-Judge evaluation, and CI/CD-gated quality pipelines.

If you are fluent in Playwright, agentic AI workflows, and modern test engineering — and want to build something genuinely new rather than maintain legacy frameworks — we invite you to join our team. ERP domain knowledge is a strong plus and will accelerate your impact.

Responsibilities:

Architect and evolve the AI-native automation framework — extending Playwright-based agents with LLM-powered planning, test generation, and self-healing capabilities.

Use AI tools extensively (Claude, GitHub Copilot, LLM APIs) to design, generate, and augment automation suites — reducing human authoring effort while increasing scenario coverage.

Build and maintain Playwright agent pipelines for end-to-end workflow automation across Deltek’s Projects, Workforce Management, and Financials modules.

Integrate LLM-as-a-Judge (LLMaaJ) evaluation into the test pipeline to automatically score AI-generated outputs, detect hallucinations, and validate response quality against golden datasets.

Design and implement AI safety and correctness test cases: hallucination detection, bias testing, output guardrail validation, and behavioral consistency across edge cases.

Own the CI/CD automation pipeline (GitHub Actions / Azure DevOps) for AI-enabled releases — including regression gates, model-response validation, and automated quality dashboards in ReportPortal and Grafana.

Validate AI/ML outputs including prediction accuracy, recommendation relevance, natural-language responses, and inference API payloads.

Build and maintain golden datasets for AI drift detection, regression baselines, and LLM evaluation benchmarks.

Collaborate with Product Managers, AI/ML Engineers, and QE leads to define AI feature release quality gates and automation coverage targets.

Mentor QE team members on AI-assisted automation patterns, agentic testing concepts, and framework best practices.

Contribute to test strategy for data migration validation of schema fidelity and record correctness.

Qualifications:

BS/MS degree in Computer Science, Software Engineering, or a related field.

Relevant certifications in software quality, AI/ML, or cloud engineering are advantageous.

Experience:

8+ years of experience in test automation engineering, with at least 3+ years working with AI/LLM-based systems or agentic automation frameworks.

Proven hands-on experience with Playwright — including Playwright agents, fixtures, and API testing integration.

Demonstrated experience using AI tools (Claude API, OpenAI, GitHub Copilot, or equivalent) to accelerate test authoring, framework design, or output evaluation.

Track record of designing and implementing AI-based automation solutions — not just using automation tools, but building the frameworks others use.

Experience integrating automation into CI/CD pipelines (GitHub Actions, Jenkins, or Azure DevOps).

Experience with performance, scalability, or data-drift testing of AI features in production or pre-production ERP contexts.

ERP domain knowledge (Project Accounting, Financials, Payroll, Time & Expense) is a strong plus and will significantly accelerate onboarding and impact.

Good-to-Have Skills:

Familiarity with Ajera, Costpoint, Vantagepoint, or comparable project-based ERP systems.

Understanding of LLM fine-tuning, RAG pipelines, vector databases, and embeddings from a QA/validation perspective.

Experience building or working with self-healing automation frameworks or AIOps tooling.

Exposure to security testing for AI systems — prompt injection, output sanitization, guardrail bypass testing.

Familiarity with data privacy and compliance frameworks in AI-enabled enterprise software.

Technical Qualifications:

Deep, hands-on proficiency with Playwright — including agentic patterns, multi-step workflow automation, and integration with LLM backends.

Proficiency in TypeScript and/or Python for building automation frameworks, AI evaluation utilities, prompt-testing harnesses, and data-driven test pipelines.

Strong understanding of LLM/ML concepts from a QA perspective: prompt engineering, hallucination detection, output scoring, explainability validation, behavioral consistency testing.

Experience with REST and GraphQL API testing, including automated evaluation of LLM inference API payloads and AI-generated JSON responses.

Familiarity with ReportPortal, Grafana, or equivalent for test execution dashboards and quality metric visualization.

Strong SQL skills for data validation, training dataset verification, and ERP data pipeline testing.

Working knowledge of GitHub Actions and Azure DevOps (ADO/TFS) for CI/CD pipeline integration and issue tracking.

Good understanding of Agile/Scrum practices and AI model release cycles — shadow mode, A/B comparison, phased rollout validation.

Soft Skills:

Framework-builder mindset: thinks in systems, not scripts — builds what others use rather than executing what others built.

Strong communication skills: able to explain AI validation concepts clearly to engineers, product managers, and QE team members.

High ownership and self-direction: identifies automation gaps proactively and drives coverage improvements without waiting to be asked.

Collaborative and generous with knowledge: invests in mentoring team members and raising the team’s automation maturity.

Continuous learner: actively tracks the evolving AI tooling ecosystem and brings new techniques into the framework.

Able to manage multiple priorities in a fast-paced, distributed team environment.

Join Deltek and be at the forefront of how modern ERP quality engineering is done. You will help build the AI driven current automation framework into an industry-leading AI-native automation platform — combining Playwright agents, LLM-powered test generation, self-healing infrastructure, and intelligent quality gates.

About US:-

We turn customer challenges into growth opportunities.

Material is a global strategy partner to the world’s most recognizable brands and innovative companies. Our people around the globe thrive by helping organizations design and deliver rewarding customer experiences.

We use deep human insights, design innovation and data to create experiences powered by modern technology. Our approaches speed engagement and growth for the companies we work with and transform relationships between businesses and the people they serve.

Srijan, a Material company, is a renowned global digital engineering firm with a reputation for solving complex technology problems using their deep technology expertise and leveraging strategic partnerships with top-tier technology partners.

Job Description: Sr. Full Stack Engineer (Python, JavaScript & AI Engineering) – 7-8 years 

Role Summary 

We are seeking an experienced Sr. Engineer/Technical Lead with strong expertise in Python, JavaScript/TypeScript, and AI-native application development. The ideal candidate will build scalable cloud applications, architect intelligent systems powered by Large Language Models (LLMs), drive engineering excellence, and help teams adopt modern AI-assisted development practices. This is a hands-on leadership role combining software engineering, AI integration, and technical mentorship. 

Key Responsibilities 

• Design, develop, and maintain scalable applications using Python and JavaScript/TypeScript. 
• Build APIs, microservices, and event-driven cloud-native solutions. 
• Design and implement AI-enabled features using LLMs, RAG, structured outputs, and tool integrations. 
• Build and maintain agentic workflows for business automation and developer productivity. 
• Leverage AI coding assistants and code agents to improve software delivery and engineering efficiency. 
• Integrate enterprise services including authentication, SSO, authorization, and internal platforms. 
• Collaborate with platform teams to deploy and operate applications on AWS or Azure. 
• Drive engineering best practices including CI/CD, testing, observability, code reviews, and secure development. 
• Document architectures, APIs, AI workflows, and key technical decisions. 
• Mentor engineers and help teams adopt modern AI-first development practices. 

Required Skills 

• Strong hands-on experience building production applications with Python. 
• Good experience with JavaScript or TypeScript and modern application architectures. 
• Experience designing REST APIs, microservices, and distributed systems. 
• Practical understanding of LLMs, prompt engineering, RAG, embeddings, vector search, and AI application patterns. 
• Experience integrating commercial or open-source AI models into production systems. 
• Hands-on experience using AI coding assistants and code agents to accelerate development. 
• Understanding of agent orchestration concepts and Model Context Protocol (MCP). 
• Experience with AWS or Azure cloud platforms. 
• Experience with CI/CD, automated testing, code quality, and application observability. 
• Strong communication, documentation, and technical leadership skills. 

Good-to-Have Skills 

• Experience with AI orchestration frameworks such as LangGraph, CrewAI, Semantic Kernel, or similar. 
• Knowledge of FastAPI, Node.js, React, or Next.js. 
• Experience with containers and Kubernetes. 
• Exposure to AI evaluation, guardrails, and production monitoring. 
• Experience mentoring teams and driving AI adoption across engineering organizations. 

Job Title : Software Development Engineer in Test (SDET)

Experience : 2 to 5 Years

Location : Bangalore

Working Days : 5 Days/Week

Notice Period : Immediate to 15 Days

Interview Process : 1 Internal Round + 2 Client Rounds

Job Summary :

We are looking for a skilled Software Development Engineer in Test (SDET) with strong expertise in Java-based automation testing. The ideal candidate should have hands-on experience in automation frameworks, API testing, debugging, SQL, and cloud technologies while ensuring the delivery of high-quality software applications.

Mandatory Skills :

Java, Selenium, Appium, API Testing, SQL, AWS, Debugging, Cache Memory Concepts (Python is a Plus).

Key Responsibilities :

• Design, develop, and maintain automated test scripts using Java and Selenium/Appium.
• Perform API testing and validate backend services.
• Write and execute SQL queries for data validation and testing.
• Debug application issues and collaborate with development teams to resolve defects.
• Work with AWS environments for testing and deployment validation.
• Validate application performance involving cache memory mechanisms.
• Contribute to improving test automation frameworks and CI/CD processes.

Required Skills :

• Strong proficiency in Java (Mandatory).
• Hands-on experience with Selenium and Appium.
• Strong knowledge of API Testing.
• Good understanding of SQL.
• Experience with AWS.
• Excellent debugging and troubleshooting skills.
• Understanding of cache memory/caching concepts.
• Python knowledge is an added advantage.

Byteridge is seeking a Business Intelligence Solutions engineer to drive

transformative analytics and AI-powered insights for our strategic customers across India. You will lead

complex deployments of Amazon QuickSuite and related AWS analytics services, working directly with

customers to accelerate their data-driven transformation.

This role combines deep technical expertise in business intelligence, data integration, and AI automation to deliver production-ready solutions that unlock the full potential of customer data across multi-cloud environments.

What You'll Do

Solution Architecture & Deployment

• Lead end-to-end deployments of Amazon QuickSuite, QuickSight, and AWS analytics solutions forstrategic customers

• Design and implement comprehensive BI architectures that integrate with diverse data sourcesacross multi-cloud environments

• Develop custom connectors, APIs, and MCP (Model Context Protocol) integrations to extendplatform capabilities

• Configure and optimize Agents, Spaces, Topics, and Dashboards for customer-specific use cases

Technical Development & Integration

• Build custom connectors and integrations to connect QuickSuite with enterprise data sources

• Develop API-based solutions and automation workflows to streamline BI operations

• Implement data pipelines connecting multi-cloud data sources (AWS, Azure, GCP) to analyticsplatforms

• Create reusable templates, accelerators, and best practices for rapid deployment

Customer Engagement & Enablement

• Partner with customer teams to understand business requirements and translate them into

technical solutions

• Provide technical guidance on dashboard design, data modeling, and visualization best practices

• Train customer teams on QuickSuite capabilities, agent configuration, and self-service analytics

• Identify expansion opportunities and drive adoption of advanced analytics features

What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, or equivalent practical

experience

• 4-6 years of experience in business intelligence, data analytics, or technical consulting roles

• Strong programming skills in Python, JavaScript, SQL, or similar languages

• Experience with BI platforms, data visualization, and analytics solution deployment

Technical Expertise (High-Level Alignment)

• Proficiency with business intelligence and data visualization tools (QuickSight, Tableau, Power BI, or

similar)

• Experience with API development, REST services, and integration patterns

• Understanding of data modeling, ETL/ELT processes, and data warehouse concepts

• Familiarity with AWS analytics services (QuickSight, Athena, Glue, Redshift) or equivalent platforms

Preferred Experience

• Hands-on experience with Amazon QuickSuite or similar AI-powered analytics platforms

• Knowledge of MCP (Model Context Protocol) and custom connector development

• Experience configuring AI agents, knowledge bases, and automated workflows

• Background working with multi-cloud data sources and hybrid architectures

• Understanding of data governance, security, and compliance requirements

Essential Attributes

• Excellent problem-solving skills with ability to navigate ambiguous requirements

• Strong communication skills to engage with technical and business stakeholders

• Ability to manage multiple customer engagements and prioritize effectively

• Customer-focused mindset with commitment to delivering measurable business outcomes

At Oracle Health, we’re building the future of healthcare

At Oracle Health, we’re building the future of healthcare—cloud-native healthcare solutions with AI at their core, designed to operate at nation-scale. Our mission is to transform how hospitals and physicians work, enabling better patient care while ensuring accurate, timely reimbursement.

We are modernizing Electronic Health Record and Clinical Analytics systems using LLMs and AI agents, helping clinicians focus more on patients and less on administrative burden.

We’re looking for highly skilled AI engineers to design and build high-scale, cloud-based data processing pipelines that ingest, transform, and analyze massive volumes of healthcare data with low latency, powering business insights and analytics across EHR and RCM systems.

You will leverage LLMs, AI agents, and modern data platforms to solve problems like clinical decision support, revenue optimization, and workflow automation while using AI-assisted development tools to accelerate delivery.

Responsibilities

Key Responsibilities

• Build and enhance data pipelines, ETL workflows, and transformations.
• Contribute to LLM/agent-based features and analytics use cases.
• Work with EHR/RCM datasets and support KPI/dashboard development.
• Learn and apply best practices in cloud, data engineering, and LLMOps.

Mandatory Qualifications

• BS/MS in Computer Science or equivalent.
• 4+ years of relevant software engineering experience.
• Strong software engineering skills in Python/Java.
• Strong knowledge of SQL.
• Deep expertise in data engineering: ETL, data transformation, data modelling (Spark, SQL), hands-on experience in BI.
• Experience building high-scale distributed data systems.
• Cloud experience (OCI/AWS/Azure).
• Experience with creating major new functionality in a software system all the way from design, through development and testing to production deployment.
• Experience with collaborating across multiple functional areas to develop components that are part of a larger system.
• Experience with LLMs, prompt engineering, and agent frameworks.
• Experience with blending hands-on coding with smart adoption of AI-driven solutions to rapidly prototype, test, iterate, and deliver reliable code.
• Experience using ChatGPT, Claude, or similar models on a routine basis to improve productivity.

Preferred Qualifications

• Experience with agentic architectures or GenAI platforms.
• Background in healthcare or digital health systems.
• Understanding of EHR systems and RCM workflows.
• Familiarity with healthcare coding standards (ICD/CPT).

Byteridge is seeking a Rapid Prototyping Engineer specializing in AI Infrastructure & Optimization to work with our most strategic customers on deploying, fine-tuning, and optimizing large language models at scale. You will be at the forefront of Byteridge's AI infrastructure capabilities, helping customers unlock the full potential of foundation models through expert-level deployment on GPU infrastructure.

This highly technical role requires deep expertise in machine learning infrastructure, GPU optimization, and production ML systems, combined with the ability to translate complex technical concepts into customer success.

What You'll Do

Model Deployment & Optimization

• Lead end-to-end deployments of large language models on AWS infrastructure for strategic

customers

• Design and implement training, fine-tuning, and inference pipelines using Amazon SageMaker AI

• Optimize model performance through GPU-level tuning, kernel optimization, and infrastructure

configuration

• Deploy models on diverse GPU architectures including NVIDIA and AWS custom silicon (Trainium,

Inferentia)

Infrastructure Architecture & Performance

• Architect scalable ML infrastructure using SageMaker AI Inference, HyperPod, and distributed

training frameworks

• Implement CUDA-level optimizations and custom kernels for improved model performance

• Design storage and networking architectures optimized for high-throughput ML workloads

• Troubleshoot and resolve complex performance bottlenecks at the GPU driver and kernel level

Customer Engagement & Technical Leadership

• Partner with AWS AI Specialist Solution Architects and customer ML teams to understand model

requirements and deployment constraints

• Provide technical guidance on model selection, fine-tuning strategies, and production best practices

• Conduct performance benchmarking and cost optimization analysis for ML workloads

• Share field insights with AWS product teams to influence infrastructure and service roadmaps

What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience (Master's or

PhD preferred)

• 5+ years of experience in machine learning infrastructure, model deployment, or GPU computing

• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX)• Deep understanding of LLM architectures, training methodologies, and inference optimization

Technical Expertise (High-Level Alignment)

• Hands-on experience training, fine-tuning, or deploying large language models in production

• Proficiency with GPU programming, CUDA, and kernel-level optimization techniques

• Experience with distributed training frameworks and multi-GPU/multi-node orchestration

• Strong knowledge of AWS core services: EC2 (GPU instances), S3, EFS, VPC, and networking

Preferred Experience

• Direct experience with Amazon SageMaker AI (Training, Inference, HyperPod) or equivalent ML

platforms

• Understanding of GPU architectures (NVIDIA A100, H100) and AWS custom silicon (Trainium,

Inferentia)

• Experience with model compression techniques (quantization, pruning, distillation)

• Knowledge of MLOps practices, model monitoring, and production ML system design

• Background in high-performance computing, distributed systems, or systems programming

Essential Attributes

• Ability to dive deep into technical problems and debug complex infrastructure issues

• Strong analytical skills with data-driven approach to optimization

• Excellent communication skills to explain complex technical concepts to diverse audiences

• Comfortable working in ambiguous, fast-paced environments with evolving requirements

• Ownership mindset with ability to drive projects from architecture to production

About Indee

Indee is a secure video streaming and distribution platform trusted by the world's largest studios, streamers, and awards bodies. Today more than 1100 companies use Indee to power screeners, awards campaigns, content sales, and secure review workflows, including partners such as Netflix, A24 Films, Amazon MGM Studios, Disney, Paramount Pictures, Universal Pictures, NBC Universal, Focus Features, Paramount Global, Neon, STARZ, and Magnolia Pictures. Indee has achieved consistent growth, averaging 60% year-on-year growth over the past five years.

About the role

We are seeking a QA Manager with 8-12 years of experience in software testing and quality assurance, including experience leading QA teams in fast-paced product environments. The ideal candidate is a hands-on quality leader with strong expertise in both manual and automation testing, a proven track record of driving high-velocity daily releases, and the ability to build and develop high-performing QA teams. This individual will be responsible for the quality strategy for Indee's products while actively contributing to release planning, testing initiatives, process improvements, automation efforts, and production quality outcomes.

Responsibilities

• Own and continuously evolve Indee's QA strategy across manual, automation, regression, exploratory, API, performance, and release testing.
• Lead QA efforts throughout the software development lifecycle, including test planning, test execution, defect management, risk assessment, release validation, and release sign-offs.
• Drive adoption of AI-enabled testing approaches and continuously evaluate opportunities to improve testing efficiency, quality, and coverage.
• Drive release quality by establishing strong validation processes, improving regression coverage, and minimizing production defects.
• Define, track, and report on key quality metrics, including production defect leakage, release readiness, automation coverage, defect trends, and test effectiveness.
• Conduct root cause analysis for production issues and implement preventive actions to improve product quality and release stability.
• Drive automation initiatives across the QA function, improving automation coverage, framework reliability, execution efficiency, and long-term maintainability.
• Partner with engineering teams to identify automation opportunities and improve testing effectiveness through API-based and UI-based automation approaches
• Mentor and develop QA engineers across manual and automation testing disciplines, supporting skill development, career growth, and technical excellence.
• Enable manual QA engineers to contribute to automation efforts through coaching, structured ownership, and ongoing support.
• Collaborate with product and engineering teams to drive quality throughout the software development lifecycle, from requirements and design through testing, release, and production support.
• Support timely investigation, validation, and resolution of customer-reported issues, production incidents, and QA-related escalations.
• Improve release planning, workload allocation, and team capacity management to support multiple concurrent projects and business priorities.
• Lead, mentor, and manage the QA team, including hiring, onboarding, performance management, capacity planning, and succession planning.
• Foster a collaborative, accountable, and high-performing team culture that promotes ownership, continuous improvement, and operational excellence.

Requirements

Education: Bachelor's degree in computer science, software engineering, or a related field; master's degree preferred.

Experience:

• 8-12 years of QA experience in product companies.
• 4+ years of experience managing/leading QA teams.

Must Haves

• Strong people leadership and planning skills
• Ability to schedule work within defined timelines for the team.
• Strong hands-on experience in QA of web and mobile applications.
• Experience in test automation using Selenium with Python, leveraging BDD frameworks.
• Experience with API testing using tools like Postman or equivalent.
• Strong understanding of test strategy, test planning, regression testing, defect management, and release validation processes.
• Experience leading QA for production releases and driving release sign-off decisions.
• Experience defining, tracking, and analyzing quality metrics and release health indicators.
• Strong understanding of root cause analysis and defect prevention methodologies.
• Experience working in Agile/Scrum environments.
• Strong stakeholder management, communication, and cross-functional collaboration skills.
• Strong capabilities in git/github
• Strong experience in JIRA, issue tracking, JIRA customization and reporting.
• Experience with Appium or mobile automation frameworks.

Good-to-haves

• Exposure to performance testing
• Understanding of ISO-27001 processes and frameworks
• Understanding of SOC-2 compliance and application / QA-specific needs.
• Exposure to security and penetration testing.
• Strong background in CI/CD pipelines

Benefits

• Competitive salary and comprehensive benefits package.
• Opportunity to work with cutting-edge technologies and industry-leading experts.
• Flexible work environment with the option for remote work for 3 weeks a month (hybrid).
• Professional development opportunities and support for continued learning.
• Dynamic and collaborative company culture with opportunities for growth and advancement.

If you are passionate about software quality and leading high-performing teams, value collaboration, and are eager to work in a respectful environment, we'd love to hear from you!

SOLARSQUARE  ·  ENGINEERING

Staff Engineer, Data Platform

Team: Data Engineering    ·    Level: Staff (Individual Contributor)    ·    Experience: 8+ years      ·    Full-time

Own the data platform that turns every customer and field interaction into a decision SolarSquare can act on.

About SolarSquare :

At SolarSquare we are building the Home-Energy brand of future India. We help homes switch to rooftop solar and move away from traditional coal electricity. We are a full-stack D2C residential solar brand — designing, installing, maintaining (after-sales), and financing solar systems for home-owners across India.

In a few short years we have scaled to become the leading residential solar brand in India. We are obsessed with quality, customer service, and innovating to make it simple for homes to switch to solar. We are looking for leaders to join us in this mission.

Get to know us

• SolarSquare - company website
• Featured by TIME as one of the World’s Top GreenTech Companies of 2025
• SolarSquare raises $53M Series C led by B Capital (Moneycontrol)
• India’s rooftop solar market and SolarSquare’s growth (TechCrunch)

About the role :

As a Staff Engineer on Data Platform, you set the technical direction for how we move, model, and serve data across the entire customer lifecycle — from real-time operational streams off thousands of field devices to the analytical layer our leaders and AI systems depend on. You operate at the scope of the platform: ambiguous problems land on your desk, and you turn them into systems the whole org builds on.

What you’ll own :

• Design and scale the data platform end to end: streaming ingestion, batch pipelines, the analytical warehouse, and a governed self-serve metrics layer.
• Build real-time operational data streams that power field operations and customer-facing experiences with low latency and high reliability.
• Own data quality, lineage, and governance — including PII handling — so teams trust the data and never dump it mindlessly.
• Define a golden metrics layer and the standards, contracts, and tooling that make analytics self-serve across the org.
• Set the bar on craft: review designs, clear data tech debt every sprint, and mentor engineers across pods.

The Tech you’ll work with :

You’ll work across event streaming (Kafka), PostgreSQL as the system of record, a columnar analytical warehouse for OLAP, Python-based pipelines, and Metabase for self-serve BI — with more workloads moving to real-time and columnar storage as we scale. We’re stack-agnostic for the right person; fundamentals matter more than any one tool.

What we’re looking for :

• 8+ years building large-scale data systems in production, with deep ownership of at least one major data platform.
• Strong command of distributed data processing and streaming architectures, plus modern columnar / analytical warehouses.
• Expert SQL and data modeling; fluency in data quality, lineage, and governance.
• Proven ability to turn ambiguous business questions into durable data models and reusable platform abstractions.
• Experience setting technical direction and growing the engineers around you.
• Customer-obsessed and impact-led: you start from the customer’s pain and judge yourself by the metric your work moves, not the tickets you close.
• High agency: you don’t wait to be told — you spot problems, pick them up, and own the outcome through to production.
• Craft over shortcuts: you fix root causes rather than symptoms, clear tech debt as you go, and don’t ship bugs.
• Bias for speed and simplicity: you build once for reuse, automate the mundane, and let AI draft the first pass so your judgment goes where it matters.
• Data-driven: you reach for evidence over assumptions and let results guide the next decision.

Bonus points

• Experience with lakehouse architectures, real-time analytics, or geospatial / IoT-scale data.
• Exposure to semantic layers and self-serve analytics platforms.
• Built data platforms that feed ML or AI systems.

Why you’ll love building here

• Direct ownership of high-impact initiatives with visible customer and business outcomes.
• An AI-native engineering culture with first-class tooling and internal agents.
• A high-agency, low-bureaucracy environment where you debate what’s right and ship.
• A meritocracy where growth and recognition track impact, not tenure.
• Competitive compensation.
• A front-row seat to putting clean energy on millions of Indian rooftops.

About Ritually

Ritually is building the definitive process discovery platform for back office work. Our product fuses underutilized system telemetry with computer vision to help large enterprise and scaling mid-market companies deeply understand and reimagine their highest value and most repetitive processes for a world where humans and agents work together. We're based in New York and Denver.

We believe deeply in trust (of our customers and each other), craft, customer obsession, and speed.

You'll be joining an AI-native, fast-moving, and repeat founding team. Ritually's founders previously built and exited a startup (Involvio) to Cisco. The company is funded and working with design partners.

The Role

This is a founding applied-AI role. You'll be building our core data pipeline and intelligence layer with the founding team from 0-1 You'll be tackling our largest technical challenges across technologies.

What You'll Do

• Design and build data pipelines that capture and turn high volumes of system activity into structured, queryable data.
• Turn raw activity streams into processes: sessionize event logs, cluster recurring sequences, and use LLMs to label and summarize what's happening.
• Build the evaluation backbone from scratch: stand up synthetic data generation pipelines that produce labeled scenarios to measure accuracy and catch regressions.
• Own data quality and privacy.
• Partner closely with the founders and the rest of engineering to ship features end to end.

What We're Looking For

• 1-4 years of experience in data engineering, AI/ML engineering, or backend work with a data focus (some of this can be project or research experience).
• Strong in Python and/or TypeScript, comfortable in SQL, and able to build data pipelines you can trust.
• Hands-on experience working with LLMs structured output, prompting, and wrangling non-determinism while keeping behavior reliable.
• A practical sense for evaluation: you know that "it looks right" isn't the same as "it's measurably right."
• Care about data privacy and handling sensitive information responsibly.
• Comfort with ambiguity and a real appetite to own a hard, open-ended problem.

Nice to Have

• Background in process mining, sequence / event-log analysis, or workflow analytics.
• Deeper PostgreSQL: window functions, partitioning, pg_cron, query performance.
• Embeddings and vector search (pgvector) or semantic retrieval.
• Familiarity with cloud infrastructure.
• Any prior early-stage startup experience.
• Degree in computer science or a related field.

About Ritually

Ritually is building the definitive process discovery platform for back office work. Our product fuses underutilized system telemetry with computer vision to help large enterprise and scaling mid-market companies deeply understand and reimagine their highest value and most repetitive processes for a world where humans and agents work together. We're based in New York and Denver.

We believe deeply in trust (of our customers and each other), craft, customer obsession, and speed.

You'll be joining an AI-native, fast-moving, and repeat founding team. Ritually's founders previously built and exited a startup (Involvio) to Cisco. The company is funded and working with design partners.

The Role

This is a founding full-stack role. You'll be building our application with the founding team from 0-1 You'll own features and infra end to end and across technologies. You'll also own how we build: ensuring our AI development workflow is fast, dependable and secure.

What You'll Do

• Build features end to end, across our desktop client, web app, and the backend services that tie them together.
• Go deep in our cross-platform Electron desktop client the native OS integration that powers on-device capture, and the on-device privacy and redaction that runs before data leaves the machine.
• Move fluidly across technologies and layers, picking up whatever a problem needs rather than staying in one corner of the stack.
• Own the infrastructure and deployment path CI/CD, releases, and the cloud services everything runs on so shipping stays routine and reliable.
• Own how we build: keep our AI development workflow fast, dependable, and secure and establish the conventions, tooling, and guardrails that let a small team build like a much larger one.
• Own observability and on-call basics logging, error tracking, and alerting so we catch issues before our customers do.
• Help set technical direction and keep the codebase legible as we scale the engineering team.

What We're Looking For

• 1-4 years building software across the stack frontend, backend, and the glue between them (internships and meaningful side projects count).
• Comfort working across multiple languages and technologies, and a genuine willingness to learn whatever a problem requires.
• Solid fundamentals in shipping production software version control, testing, debugging, and deployment.
• Experience with, or strong interest in, owning infrastructure and devops: CI/CD, cloud services, and reliability.
• Genuine excitement about AI-native development you've used AI coding agents and want to push how far they can go.
• Comfort with ambiguity and a willingness to own problems end to end in a small team.

Nice to Have

• Experience building desktop applications (Electron or native).
• Experience building internal tooling or automation that made a team measurably faster.
• Experience building applications for on-premise deployment.
• Familiarity with managed backend platforms and AI agent tooling.
• Any prior early-stage startup experience.
• Degree in computer science or a related field.

Primary Skills

• Observability: ELK (Elasticsearch/Kibana), Prometheus, Grafana, PromQL
• Automation: Java/Vert.x or Python (FastAPI), Shell/Bash, REST/SOAP APIs
• Cloud & Platform: Docker, Kubernetes, Kafka, Redis
• Reliability Engineering: Distributed Systems, Microservices, Event-Driven Architecture, DR & Incident Management
• Stakeholder Management & Cross-functional Collaboration

Secondary Skills

• Agentic AI: LangChain, LangGraph, RAG, MCP
• LLM Integration & AI Frameworks
• Python (FastAPI)

Key Responsibilities

• Build and deploy LLM-powered Agentic AI solutions with tool calling and autonomous workflows.
• Integrate AI capabilities into existing applications using modern AI frameworks.
• Own platform reliability through SLAs, SLOs, error budgets, MTTD/MTTR, and operational governance.
• Enhance observability using ELK, Prometheus, Grafana, and advanced alerting.
• Lead incident response, RCA, disaster recovery, and resiliency initiatives.
• Drive production readiness, automation, platform stability, and infrastructure optimization.

JOB DESCRIPTION-

Exp - 5 to 8yrs 

Job Summary

We are looking for a highly skilled and motivated Senior Software Engineer with strong expertise in Java (primary) and working knowledge of Python. The ideal candidate will be responsible for designing, developing, and maintaining scalable backend systems, while contributing to high-quality software delivery across the full development lifecycle.

Key Responsibilities

• Design, develop, and maintain robust, scalable, and high-performance applications using Java (Spring Boot / Microservices architecture)
• Develop reusable components and APIs with a focus on performance, security, and scalability
• Leverage Python for automation, scripting, data processing, or ML-related use cases (as applicable)
• Collaborate with cross-functional teams including Product, QA, DevOps, and Architecture
• Participate in system design discussions and contribute to technical decision-making
• Write clean, efficient, and well-documented code following coding standards and best practices
• Optimize applications for maximum speed and scalability
• Troubleshoot and debug complex production issues
• Contribute to CI/CD pipelines and DevOps practices
• Mentor junior engineers and perform code reviews

Required Skills & Qualifications

Technical Skills

• Strong hands-on experience in Core Java, Spring Boot, and Microservices architecture
• Solid understanding of RESTful APIs, multithreading, concurrency, and JVM performance tuning
• Practical experience with Python (automation, scripting, or backend development)
• Experience with databases: SQL (MySQL, PostgreSQL) and/or NoSQL (MongoDB, Cassandra)
• Familiarity with cloud platforms (AWS, Azure, or GCP)
• Strong knowledge of data structures, algorithms, and system design
• Experience with message brokers (Kafka, RabbitMQ)
• Exposure to containerization & orchestration (Docker, Kubernetes)
• Experience with version control systems (Git)

Preferred Skills

• Experience in distributed systems and event-driven architectures
• Knowledge of Python frameworks (Flask, FastAPI, Django)
• Exposure to big data technologies (Spark, Hadoop) or ML workflows
• Experience with CI/CD tools (Jenkins, GitHub Actions, etc.)
• Familiarity with observability tools (Prometheus, Grafana, ELK stack)

Soft Skills

• Strong problem-solving and analytical skills
• Excellent communication and collaboration abilities
• Ability to work in a fast-paced agile environment
• Proactive ownership and accountability

Product Engineer

Product Engineer | Fibr.ai

Bengaluru · In office · 2-6 years Stack: Python · FastAPI · Temporal · PostgreSQL · MongoDB

The role Fibr is building the agentic web experience layer - turning every URL into an intelligent agent that senses intent, makes decisions, and adapts in real time. Our agents personalise the full journey, running long LLM workflows against live customer accounts and millions of sessions.

You'll own features end-to-end - from the rough idea in a Slack thread to something shipped, instrumented, and behaving correctly in production. New surface areas land on your plate every few weeks: a new agent, a new integration, a new optimization loop. You're responsible for the whole thing, including the evals and metrics that prove it works. You'll work directly with the founding team and ship to real users every week.

What you'll do Ship AI-powered features end-to-end - backend, data, LLM layer, and the surface the user sees Design long-running workflows that hold up against rate limits, partial failures, and noisy third-party APIs Build and maintain the evals, guardrails, and instrumentation that decide whether a feature is good enough to ship Model the data behind agents and the analytics behind product decisions Sit in on architecture calls and shape where the platform goes next

Must-haves 2-6 years of production backend experience Has shipped LLM-powered features to real users in production - not demos, not side projects. Be ready to talk about what broke and how you fixed it Has built and run evals for LLM systems. Show us the harness, the dataset, and the decisions it drove Comfortable across relational and document databases Has worked with a durable workflow or queue system in production Ships fast without breaking the build Nice-to-haves RAG, vector stores, or tool-use / multi-step agents in production Experience with rate-limited third-party APIs at scale (ad platforms, CRMs, analytics) Strong product sense - you catch the UX issue before the user does Time spent at an early-stage startup

How we work High ownership, low bureaucracy. Decisions in the room, not in docs. You'll work directly with the founding team.

Why Fibr AI Competitive salary + meaningful early-stage equity A chance to build deep expertise at the frontier of AI product

Job Title: Lead Data Scientist

Department: Data Science

Location: Bengaluru

About StepOut

Sports have an access problem. For decades, elite performance intelligence, tactical analysis, and scouting infrastructure have been accessible only to the top clubs. Everyone else has been left behind. StepOut is changing that.

We are building an AI-powered football intelligence platform that transforms raw match footage into structured performance data, tactical insights, and scouting intelligence using proprietary computer vision and machine learning.

We are building this from India, while our technology is being used by clubs like Real Madrid and AFC Ajax, along with leading football ecosystems across 29 countries globally.

If football means something to you beyond entertainment, this might be your place.

The Role

We’re looking for a Lead Data Scientist to help build intelligent systems that understand football at scale.

This is not a research-only role. This is not a notebook-only role.

This is an innovative builder’s role.

You will create production-grade machine learning systems that directly influence how clubs, coaches, scouts, and players make decisions.

As a lead, your role goes beyond building models. You will define technical direction, shape the data science function, mentor talent, and help create the foundations of what this team becomes.

What You’ll Do

• Build and deploy end-to-end ML systems for football intelligence products
• Translate football concepts into scalable data models, metrics, and decision systems
• Own the full ML lifecycle: experimentation, deployment, monitoring, and iteration
• Work closely with Product, Engineering, and Computer Vision teams to solve real-world problems
• Debug messy, imperfect data and design reliable analytical pipelines
• Define technical direction for the data science function
• Mentor junior team members and raise engineering and analytical standards
• Help hire and shape the future data science team
• Drive prioritization and decision-making in ambiguous, fast-moving environments
• Constantly engage in learning new and upcoming research topics and subjects in sports analytics
• Obtain a deep and implementational level understanding of established advanced analytical research areas and models

Must-Haves

• Strong ML fundamentals across supervised and unsupervised learning, experimentation, and model evaluation
• Strong Python, SQL, data analysis, and production engineering mindset
• Experience taking ML systems from idea to production
• Strong ownership, judgment, and decision-making ability
• Ability to communicate clearly with both technical and business stakeholders

Football Passion (Mandatory)

• You must actively follow football and genuinely understand the game.
• Formations, tactical systems, player roles, match flow, performance context - these should feel natural to you.

Good to Have

• Computer vision experience (YOLO, tracking, PyTorch, TensorFlow)
• Sports analytics experience
• LLM or agentic AI experience
• Public ML or football analytics work (GitHub, blogs, research)

Who Will Thrive Here

This role is for someone who sees football as more than just a sport.

Someone who debates tactics, spots patterns others miss, and gets excited by the idea of building technology that changes how the game is understood.

You’ll thrive here if you:

• Love football deeply, not casually
• Love building from scratch
• Thrive in ambiguity and move fast without waiting for perfect instructions
• Want ownership, accountability, and meaningful impact
• Get excited by the idea of your work being used by elite football organizations
• Believe technology can fundamentally reshape sport
• Want to be part of something bigger than just another job

Why StepOut

Because opportunities like this are rare.

Where else can you:

• Build cutting-edge AI for football
• Solve hard problems at the intersection of sport and technology
• Create products used by elite clubs globally
• Build a global company from India
• Shape an entire function from the ground up
• Contribute to a mission bigger than business

We are building from a country ranked 142nd in world football, with the belief that world-class football infrastructure can be built from here. 

But this is bigger than software. 

Our long-term dream is to help build the infrastructure that contributes to India playing in a FIFA World Cup.

If that sounds unrealistic, even better.

“The people who are crazy enough to think they can change the world are the ones who do.” – Steve Jobs

At StepOut, we are building technology that sits at the cutting edge of football and artificial intelligence. If you are ready to contribute your precision and curiosity to a team that is reshaping how the game is understood — this is your opportunity⚽

We are looking for a passionate Backend Developer Intern (Paid Internship - 6 Months) with proficiency in Node.js, Python, PHP, and Laravel, along with working knowledge of React.js. Candidates should have prior internship experience, familiarity with AI-powered development tools, and strong problem-solving skills. Kannada-speaking candidates will be preferred.

Junior Data Scientist (2–3 Years Experience)

• Strong understanding of Probability & Statistics
• Strong educational background in Statistics or Mathematics (degree/course specialization). 
• Knowledge of core Machine Learning algorithms
• Proficiency in Python
• Experience with Natural Language Processing (NLP)
• Understanding of Transformer-based models
• 2–3 years of hands-on Data Science experience
• Good analytical and problem-solving skills

Senior Data Scientist (ML) – 5+ Years

Required Skills:

• 5+ years of experience in Data Science/ML
• Strong knowledge of Probability & Statistics
• Strong educational background in Statistics or Mathematics (degree/course specialization). 
• Good understanding of core Machine Learning algorithms
• Proficiency in Python, PySpark, and SQL
• Experience with Databricks, Azure ML, SageMaker, or Vertex AI
• Hands-on experience in Natural Language Processing (NLP)
• Understanding of Transformer-based models and architectures
• Ability to build, deploy, and optimize ML solutions at scale