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AI/ML Engineer - Generative AI GenAI

Jnanasethu IT Labs (OPC) Private Limited

  • Bengaluru, India
  • Competitive Package (Best in Industry)
  • 6-10 Yrs
  • Posted Oct 24, 2026
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About the role

We're Hiring: AI/ML Engineer Generative AI (GenAI) Company: Jnanasethu IT Labs Private Limited Job Title: AI/ML Engineer Generative AI (GenAI) Job Location: Bengaluru, Karnataka Experience: 610 Years Employment Type: Full-time Industry: IT Services & Consulting / Software Development Department: Engineering โ€“ AI/ML & Generative AI About the Role Jnanasethu IT Labs Private Limited is looking for an experienced AI/ML Engineer โ€“ Generative AI (GenAI) to design, develop, deploy, and optimize scalable, production-ready AI applications. The ideal candidate will have strong hands-on expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, Python, LangChain, LangGraph, and AWS cloud services. You will work on developing intelligent AI solutions, building enterprise-grade GenAI applications, implementing agentic workflows, and deploying secure, scalable cloud-native services. Key Responsibilities Design, develop, and deploy Generative AI applications using LLMs and RAG architectures. Build and optimize RAG pipelines, including document ingestion, chunking, embeddings, retrieval, and response generation. Integrate LLM APIs, including OpenAI and Anthropic Claude, into enterprise applications. Implement vector databases, semantic search, and efficient information retrieval solutions. Develop AI agents and intelligent workflows using LangChain and LangGraph. Implement LLM monitoring, tracing, and observability using Langfuse or similar tools. Develop Python-based microservices and REST APIs for AI application integration. Deploy and manage applications using AWS Lambda, ECS, Fargate, S3, DynamoDB, and OpenSearch. Work with SQL and NoSQL databases for data storage, indexing, querying, and retrieval. Monitor and optimize application performance, response latency, reliability, and operational costs. Support CI/CD automation, containerization, and infrastructure provisioning. Collaborate with cross-functional teams to deliver secure, scalable, production-ready AI solutions. Required Technical Skills Generative AI & LLMs Hands-on experience developing Generative AI applications. Strong understanding of RAG, embeddings, vector search, semantic retrieval, and prompt engineering. Experience integrating OpenAI and Anthropic Claude APIs. Understanding of LLM evaluation, reliability, and performance optimization. Python & AI Frameworks Strong proficiency in Python programming. Hands-on experience with LangChain, LangGraph, and OpenAI SDKs. Experience developing REST APIs and integrating external services. Monitoring & Observability Experience with LLM tracing, monitoring, and debugging. Familiarity with Langfuse or similar observability platforms. Ability to monitor token usage, latency, errors, and application performance. AWS Cloud & Deployment Working knowledge of AWS Lambda, Amazon ECS, AWS Fargate, Amazon S3, Amazon DynamoDB, and Amazon OpenSearch Service. Understanding of cloud-native application architecture, deployment, and scalability. Databases Basic to intermediate knowledge of SQL and relational databases. Familiarity with NoSQL databases, data modeling, indexing, and querying. Good to Have Experience with CI/CD pipelines using Azure DevOps. Basic knowledge of Terraform and Infrastructure as Code (IaC). Experience with Docker and containerized application deployments. Understanding of cloud security, application monitoring, and production deployment best practices. Eligibility Criteria 6โ€“10 years of relevant experience in software engineering, AI/ML engineering, Python development, or related technical roles. Demonstrated hands-on experience building and deploying GenAI applications. Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, or a related discipline, or equivalent practical experience. Strong analytical, problem-solving, and debugging skills. Ability to translate business requirements into practical AI solutions. Comfortable working in a collaborative, agile development environment. Why Join Jnanasethu IT Labs? Work on innovative Generative AI and enterprise AI applications. Contribute to the development of intelligent, scalable, cloud-native solutions. Collaborate with technology professionals on real-world AI engineering challenges. Build expertise in emerging AI technologies, LLMs, and agentic AI systems. Interested candidates can apply through Naukri with their updated resume highlighting their experience in Generative AI, RAG, Python, LangChain/LangGraph, and AWS. Join Jnanasethu IT Labs Private Limited and help build the next generation of intelligent AI solutions!

Eligibility & process

Who can apply

Experience: 6-10 Yrs. Open to matching qualifications.

Skills & stack

Iac SQL CI/CD DBMS AWS Gen Python Development Python

Selection process

  1. Online Assessment / Technical Interview Rounds / HR Review

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Iac, SQL, CI/CD, DBMS, AWS, Gen, Python Development, Python) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Jnanasethu IT Labs (OPC) Private Limited Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join Jnanasethu IT Labs (OPC) Private Limited as a AI/ML Engineer - Generative AI GenAI?
Highlight Jnanasethu IT Labs (OPC) Private Limited's market reputation, recent tech innovations, and how your skills in Iac directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Jnanasethu IT Labs (OPC) Private Limited Competitive Package (Best in Industry)
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