Job Description
The Agentic AI Engineer is responsible for building intelligent, autonomous, and collaborative AI systems. This role focuses on agent reasoning, A2A (Agent to Agent) collaboration, MCP based tool interoperability, structured output validation, and guardrailed execution suitable for production and enterprise environments.

Core Technical Skills:-
Strong proficiency in Python (mandatory)Hands on experience with agent frameworks (e.g.Autogen, LangChain, LangGraph, CrewAI etc). Preferred framework - Microsoft Azure AI Foundry Experience implementing A2A workflows (multi agent messaging, task delegation, agent roles)Practical experience with MCP Server and MCP Client development Exposing tools via MCP serversConsuming MCP tools from agentsManaging context, schemas, and permissionsDeep understanding of prompt engineering and agent reasoning patternsExperience with vector databases (eg., Chroma, Weaviate,



Azure AI Search)Strong knowledge of RAG architectures and embeddingsExperience with REST / async APIs / event driven systems

Software Engineering & Platform SkillsCloud experience (Azure preferred; AWS/GCP acceptable)Autogen, Microsoft Agent FrameworkStrong understanding of distributed systems and scalabilityGit based workflows, CI/CD and code quality practicesObservability, logging, evaluation metrics for agentic systems

Nice to Have / Preferred Skills:-
Advanced multi agent orchestration and energetic role assignmentExperience with LLMOps / AgentOps toolingKnowledge of knowledge graphs Experience building enterprise grade workflow automation agentsExposure to security considerations in agentic systems (prompt injection, tool misuse)Exposure to GuardrailsExposure to Telecom Network domainCertifications – Azure AI-900, AI-901, AI-102, AI-103

📌 Agentic AI II 4 to 6 Years II Bengaluru
🏢 Capgemini
📍 Bengaluru