Tcs Hiring For Agentic AI Engineer

Job description

Job Description: Agentic AI Engineer / Developer Job Title: Agentic AI Engineer Experience: 5 to 15 Years Location: Chennai Job Type: Full Time Job Summary We are seeking experienced Agentic AI professionals to design, develop, and deploy autonomous AI systems leveraging Large Language Models (LLMs), Agent Frameworks, RAG architectures, and enterprise AI solutions. The ideal candidate will have strong expertise in AI agent orchestration, reasoning systems, tool integration, and scalable AI deployments. Key Responsibilities • Design and develop Agentic AI solutions with autonomous decision-making, planning, reasoning, and task execution capabilities. • Build and manage AI agents using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar platforms. • Develop multi-agent and single-agent workflows with orchestration, memory management, and state handling. • Implement Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge repositories. • Integrate external tools and enterprise systems using APIs, function calling, and Model Context Protocol (MCP). • Design AI guardrails, Responsible AI controls, security policies, and Human-in-the-Loop mechanisms. • Monitor and optimize agent performance through AgentOps, observability, tracing, feedback loops, and evaluation frameworks. • Deploy and scale AI applications on cloud platforms using containers, Kubernetes/OpenShift, and CI/CD pipelines. • Collaborate with business stakeholders to identify automation and AI transformation opportunities. Required Skills Mandatory • Strong knowledge of Generative AI, LLMs, Prompt Engineering, and Agentic AI concepts. • Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalent frameworks. • Experience in RAG implementation and Vector Databases (FAISS, Pinecone, ChromaDB, Weaviate, Azure AI Search). • Proficiency in Python programming. • Experience with REST APIs, tool/function calling, and AI workflow orchestration. • Understanding of MCP (Model Context Protocol). • Knowledge of AI governance, Responsible AI, and security best practices. • Experience deploying AI applications on Azure, AWS, or GCP. Preferred • Knowledge of MLOps/LLMOps practices. • Experience with Kubernetes, Docker, OpenShift, and CI/CD. • Exposure to multi-agent systems and enterprise AI architecture. • Experience with monitoring tools and AgentOps frameworks.