Walk-in | Agentic AI engineer

Tata Consultancy Services; Chennai District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Tata Consultancy Services seeks a skilled AI engineer to architect agentic systems across enterprise workflows. You will design AI agents, define goals, decompose tasks, and implement autonomous loops using LLMs, tools, memory, and orchestration.

Strong Python/Java/.NET skills and a track record with agent frameworks are required. Join a global team focused on scalable deployments, observability, security, and responsible AI guardrails, with emphasis on production-grade tooling and cloud-native

Qualifications

• Strong understanding of agentic AI fundamentals and autonomous action loops.
• Experience building agentic workflows with LLMs, tool calling, memory, and orchestration.

Responsibilities

• Design and implement agentic AI systems for complex enterprise tasks.

Skills

Agentic AI fundamentals

LLM-driven workflows

Agent frameworks (LangChain)

MCP tool/context integration

RAG pipelines & grounding

Agent observability/AgentOps

Cloud/Kubernetes/CI-CD

Responsible AI & guardrails

Programming: Python/Java/.NET

Tools

LangChain-based agents

MCP servers

Job description

• Strong understanding of agentic AI fundamentalsgoal definition, planning, reasoning, task decomposition, and autonomous action loops.
• Design and build agentic workflows using LLMs, including tool/function calling, state management, memory, and orchestration patterns (single-agent/multi-agent).
• Hands-on experience with agent frameworks and patterns (e.g., LangChain-based agent frameworks or equivalents), including routing, workflows, and agent coordination.
• Model Context Protocol (MCP) proficiency for integrating tools and contextual data into agent workflows (tool discovery/usage via MCP servers).
• Build Retrieval-Augmented Generation (RAG) pipelines and gr ounding strategies for enterprise knowledge sources (e.g., internal repos/wikis/ticketing/content stores) to improve agent reliability.
• Agent observability & monitoring (AgentOps): track agent behavior, tool calls, outcomes, and quality signals; implement alerts/traces and feedback loops for continuous improvement.
• Cloud and/or platform engineering exposure for deploying agentic systems at scale (containers/Kubernetes/OpenShift, CI/CD, performance tuning, and secure operations).
• Responsible AI & guardrails: design human-in-the-loop controls, safe tool access, and security-aware policies for agents operating with credentials, data access, and budgets.
• Proficiency in programming languages such as Python, .Net or Java, with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Keras).