KASHII UPDATEZ Everyday Student Requirements & Python Coding Tutorials by Python Kashi
REQUIREMENT_ID_2123 • 3-DAY_ACTIVE_POLICY N

AI/ML Engineer - Generative AI GenAI

Company
Company Jnanasethu IT Labs (OPC) Private Limited
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary Competitive Package (Best in Industry)
Location
Location Bengaluru, India
Posted Date
Posted Date Today
Apply on Official Website ↗
Iac SQL Continuous Integration Continuous Integration DBMS AWS Gen Python Development
📖
Aptitude Practice Questions & Mock Tests Open Resource ↗
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
🎯
Company-Specific Interview Preparation Corner Open Resource ↗
Detailed interview experiences, exam formats, and previous test questions for Jnanasethu IT Labs (OPC) Private Limited and tech roles.
📝
Technical Placement Cheat Sheets & Question Bank Open Resource ↗
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
💻
Algorithm, DSA & Live Code Debugger Practice Open Resource ↗
Hands-on problem sets to improve coding speed and step-by-step memory debugging.

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

1
Online Assessment / Technical Interview Rounds / HR Review
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 – AI/ML & Generative AI About the Role Jnanasethu IT Labs Private Limited is looking for an experienced AI/ML Engineer – 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 6–10 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!

Jnanasethu IT Labs (OPC) Private Limited — Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC 📖
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource ↗
COMPANY GUIDE 🎯
Jnanasethu IT Labs (OPC) Private Limited Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Jnanasethu IT Labs (OPC) Private Limited and off-campus tech roles.

Open Resource ↗
MOCK TESTS & PAPERS 📝
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource ↗
CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource ↗
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, Continuous Integration, Continuous Integration, DBMS, AWS, Gen, Python Development) & 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.
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.
Why do you want to join Jnanasethu IT Labs (OPC) Private Limited as a AI/ML Engineer - Generative AI GenAI?
Preparation Tip: 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.
Preparation Tip: 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?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

More Fresh Requirements in Software Engineering

View Category Feed ↗
Jnanasethu IT Labs (OPC) Private Limited
AI/ML Engineer - Generative AI GenAI
Apply ↗
Chat Chat with Kashii