Role description

AI Engineer – Agentic AI & Advanced RAG

Exp- 8-12 Years

Key Responsibilities

AI Application Development

- Design, develop, and deploy GenAI and Agentic AI solutions using modern LLM frameworks and tools.
- Build intelligent AI agents capable of reasoning, planning, tool execution, and workflow automation.
- Develop scalable backend services and APIs for AI applications using Python and FastAPI.
- Translate business requirements into robust AI-powered solutions.

Agentic AI Development

- Develop and maintain AI agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Google ADK.
- Implement agent workflows involving task decomposition, memory management, reasoning, and tool integration.
- Build and support multi-agent collaboration patterns and orchestration workflows.
- Integrate external tools, APIs, databases, and enterprise applications into agent ecosystems.

Advanced RAG Implementation

- Design and implement Retrieval-Augmented Generation (RAG) pipelines to improve AI response quality and accuracy.
- Build document ingestion, chunking, embedding generation, retrieval, and response synthesis workflows.
- Implement advanced retrieval techniques including hybrid search, semantic search, metadata filtering, and agentic retrieval.
- Integrate enterprise knowledge repositories and structured/unstructured data sources into AI applications.

Knowledge & Data Engineering

- Develop and maintain vector database and semantic search solutions using Pinecone, FAISS, ChromaDB, or other vector stores.
- Work with Knowledge Graphs and metadata-driven architectures to enhance contextual reasoning.
- Implement memory and context management strategies for AI agents.

AI Evaluation & Observability

- Develop automated evaluation frameworks for AI applications.
- Measure performance using metrics such as answer relevance, faithfulness, hallucination detection, latency, and user satisfaction.
- Utilize tools such as RAGAS, DeepEval, LangSmith, Langfuse, and Arize AI.
- Monitor production AI systems and proactively identify quality, reliability, and performance issues.

Engineering Excellence

- Write clean, scalable, and production-ready code following engineering best practices.
- Participate in code reviews, architecture discussions, and design workshops.
- Support CI/CD implementation and deployment automation for AI solutions.
- Troubleshoot and optimize AI applications for performance, scalability, and reliability.

We are seeking a highly skilled AI Engineer with expertise in Generative AI, Agentic AI, and Advanced RAG architectures. The ideal candidate will be responsible for developing enterprise-grade AI applications, intelligent AI agents, and scalable AI platforms that leverage Large Language Models (LLMs), knowledge systems, and agent orchestration frameworks.



You will work closely with business and technology teams to build innovative AI-powered solutions that drive automation, productivity, and business value.

Key Responsibilities

AI Application Development

- Design, develop, and deploy GenAI and Agentic AI solutions using contemporary LLM frameworks and tools.
- Build intelligent AI agents capable of reasoning, planning, tool execution, and workflow automation.
- Develop scalable backend services and APIs for AI applications using Python and FastAPI.
- Translate business requirements into robust AI-powered solutions.

Agentic AI Development

- Develop and maintain AI agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Google ADK.
- Implement agent workflows involving task decomposition, memory management, reasoning, and tool integration.
- Build and support multi-agent collaboration patterns and orchestration workflows.
- Integrate external tools, APIs, databases, and enterprise applications into agent ecosystems.

Advanced RAG Implementation

- Design and implement Retrieval-Augmented Generation (RAG) pipelines to improve AI response quality and accuracy.
- Build document ingestion, chunking, embedding generation, retrieval, and response synthesis workflows.
- Implement advanced retrieval techniques including hybrid search, semantic search, metadata filtering, and agentic retrieval.
- Integrate enterprise knowledge repositories and structured/unstructured data sources into AI applications.

Knowledge & Data Engineering

- Develop and maintain vector database and semantic search solutions using Pinecone, FAISS, ChromaDB, or other vector stores.
- Work with Knowledge Graphs and metadata-driven architectures to enhance contextual reasoning.
- Implement memory and context management strategies for AI agents.

AI Evaluation & Observability

- Develop automated evaluation frameworks for AI applications.
- Measure performance using metrics such as answer relevance, faithfulness, hallucination detection, latency, and user satisfaction.
- Utilize tools such as RAGAS, DeepEval, LangSmith, Langfuse, and Arize AI.
- Monitor production AI systems and proactively identify quality, reliability, and performance issues.

Engineering Excellence

- Write clean, scalable, and production-ready code following engineering best practices.
- Participate in code reviews, architecture discussions, and design workshops.
- Support CI/CD implementation and deployment automation for AI solutions.
- Troubleshoot and optimize AI applications for performance, scalability, and reliability.

Required Skills & Qualifications





Programming & Development

- Strong hands-on development experience in Python.
- Experience developing REST APIs and microservices using FastAPI.
- Strong understanding of software engineering best practices, testing frameworks, and API development.

Agent Frameworks

- Hands-on experience in one or more of the following:
- LangChain
- LangGraph
- AutoGen
- CrewAI
- Google ADK

- Experience building AI agents and agentic workflows.

Generative AI & RAG

- Strong experience implementing Advanced RAG solutions.
- Understanding of embeddings, semantic search, vector retrieval, re-ranking, hybrid search, and prompt engineering.
- Experience integrating enterprise knowledge sources into GenAI applications.

Multi-Agent Systems

- Knowledge of multi-agent architectures and agent orchestration patterns.
- Experience implementing tool calling, workflow automation, and agent collaboration mechanisms.

Vector Databases

- Experience with one or more vector databases:
- Pinecone
- FAISS
- ChromaDB
- Weaviate
- Milvus

AI Evaluation & Observability

- Hands-on experience with:
- RAGAS
- DeepEval
- LangSmith
- Langfuse
- Arize AI

- Understanding of evaluation methodologies for LLM and RAG applications.

Emerging AI Technologies

- Knowledge of:
- MCP (Model Context Protocol)
- Knowledge Graphs
- Agent Memory Patterns
- Function Calling and Tool Integration

Skills

Mandatory Skills : AI/Generative AI, Azure AI, GenAI - LLMOps, Python

About LTM
LTM is an AI-centric global technology services company and the Business Creativity partner to the world’s largest and most disruptive enterprises. We bring human insights and intelligent systems together to help clients create greater value at the intersection of technology and domain expertise. Our capabilities span integrated operations, transformation, and business AI — enabling new ways of working, new productivity paradigms, and new roads to value. Together with over 87,000 employees across 40 countries and our global network of partners, LTM — a Larsen & Toubro company — owns business outcomes for our clients, helping them not just outperform the market, but to Outcreate it. Please also note that neither LTM nor any of its authorized recruitment agencies/partners charge any candidate registration fee or any other fees from talent (candidates) towards appearing for an interview or securing employment/internship. Candidates shall be solely responsible for verifying the credentials of any agency/consultant that claims to be working with LTM for recruitment. Please note that anyone who relies on the representations made by fraudulent employment agencies does so at their own risk, and LTM disclaims any liability in case of loss or damage suffered as a consequence of the same. Recruitment Fraud Alert - https://www.ltm.com/careers/recruitment-fraud-alert

📌 Senior Specialist - Data Sciences (India)
🏢 LTM
📍 India