T
Agentic AI Engineer
T
Agentic AI Engineer
Tata Consultancy Services- Posted 19 days ago
- Over 100 applicants have applied
Job Description
- · Strong understanding of agentic AI fundamentals—goal 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).
More Info
Key Skills
human-in-the-loop controls
platform engineering
LangChain-based agent frameworks
agentic AI fundamentals
secure operations
tool function calling
LLMs
AgentOps
memory and orchestration patterns
agent observability monitoring
agent coordination
routing workflows
Responsible AI guardrails
Containers
About Company
Skills:
snowflake , PostgreSQL, Sql, Docker, Microsoft Azure, Databricks, FastAPI, Python, Model Context Protocol, pgvector, Claude Code, Vector database, Azure AI Foundry, GitHub workflows, LangGraph, Pydantic, Azure AI Search