Agentic AI Architect-D

Capgemini Engineering; Gurugram District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Capgemini Engineering is seeking a senior AI platform specialist to design and scale enterprise-grade Agentic AI solutions. You will work with LangGraph, LangChain, and model-context protocols, building robust workflows, governance, and observability for production systems.

This role requires deep knowledge of RAG, vector databases, embeddings, and security controls, along with strong leadership and stakeholder communication to align AI initiatives with business needs.

Qualifications

• Strong hands-on experience with advanced agent architectures and agentic workflows.
• Experience implementing LangGraph, LangChain, and model context protocols.
• Experience with Bedrock-hosted models or Azure OpenAI is preferred.
• Solid understanding of RAG architectures and enterprise knowledge systems.
• Familiarity with vector databases such as Chroma and Weaviate.
• Knowledge of embeddings, semantic search, retrieval optimization, and contextual AI patterns.
• Experience building production-grade Agentic AI platforms.
• Exposure to AgentOps, AI observability, and AI governance frameworks.
• Ability to design scalable enterprise AI solutions integrated with business applications and external systems.
• Awareness of security controls and responsible AI practices.
• Strong communication, stakeholder management, and technical leadership skills.

Skills

Multi-Agent Architectures

Agentic Workflows

Agent Orchestration

Agent Memory Patterns

Planning and Reflection Frameworks

Agent Evaluation Frameworks

Agent Guardrails

Safety Controls

LangGraph

LangChain

Model Context Protocol (MCP)

A2A Protocol

Tool Calling Frameworks

Bedrock-hosted models

Azure OpenAI

RAG architectures

Vector databases

Chroma

Weaviate

Embeddings

Semantic search

Retrieval optimization

Contextual AI patterns

Production-grade Agentic AI platforms

AgentOps

AI observability

AI governance frameworks

Security controls

Responsible AI

Communication & stakeholder management

Technical leadership

Tools

LangGraph

LangChain

Google ADK

MCP (Model Context Protocol)

A2A Protocol

Tool Calling Frameworks

Bedrock-hosted models

Azure OpenAI

Chroma

Weaviate

Job description

• Strong hands-on experience in Multi-Agent Architectures, Agentic Workflows, Agent Orchestration, Agent Memory Patterns, Planning and Reflection Frameworks, Agent Evaluation Frameworks, Agent Guardrails and Safety Controls
• Hands-on implementation experience with LangGraph, LangChain, Google ADK, MCP (Model Context Protocol), A2A Protocol, Tool Calling Frameworks
• Experience working with Bedrock-hosted models (preferred) or Azure OpenAI.
• Strong understanding of RAG architectures and enterprise knowledge systems. Experience with vector databases such as Chroma and Weaviate.
• Knowledge of embeddings, semantic search, retrieval optimization, and contextual AI patterns.
• Experience building production-grade Agentic AI platforms.
• Knowledge of AgentOps, AI observability, and AI governance frameworks.
• Experience designing scalable enterprise AI solutions integrated with business applications and external systems.
• Exposure to security controls and responsible AI implementation practices.
• Strong communication, stakeholder management, and technical leadership skills.