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 servers

Consuming MCP tools from agents

Managing context, schemas, and permissions

Deep understanding of prompt engineering and agent reasoning patterns

Experience with vector databases (eg., Chroma, Weaviate, Azure AI Search)

Strong knowledge of RAG architectures and embeddings





Experience with REST / async APIs / event driven systems

Software Engineering & Platform Skills

Cloud experience (Azure preferred; AWS/GCP acceptable)

Autogen, Microsoft Agent Framework

Strong understanding of distributed systems and scalability

Git based workflows, CI/CD and code quality practices

Observability, logging, evaluation metrics for agentic systems

Nice to Have / Preferred Skills:-

Advanced multi agent orchestration and agile role assignment

Experience with LLMOps / AgentOps tooling

Knowledge of knowledge graphs

Experience building enterprise grade workflow automation agents

Exposure to security considerations in agentic systems (prompt injection, tool misuse)

Exposure to Guardrails

Exposure to Telecom Network domain

Certifications – Azure AI-900, AI-901, AI-102, AI-103

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