Agentic AI Architect-D

Capgemini Engineering; Gurugram District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Capgemini Engineering seeks a senior AI architect to lead the development of agent-based systems. You will design and implement scalable agent architectures, memory patterns and planning frameworks for enterprise integration.

You will collaborate with stakeholders, drive governance and safety controls, and oversee end-to-end deployment with responsible AI practices across Bedrock or Azure OpenAI environments.

Qualifications

• Experience in building enterprise AI platforms with agent-based architectures.
• Hands-on with LangGraph, LangChain and related toolkits.
• Strong understanding of RAG and vector databases for knowledge systems.
• Proven ability to design governance, security controls and observability for AI systems.

Responsibilities

• Design and implement scalable agent-based platforms for enterprise apps.
• Collaborate with stakeholders to align AI capabilities with business goals.
• Lead architecture decisions on memory, planning, evaluation, and guardrails.
• Ensure compliance with security, governance and responsible AI practices.

Skills

Multi-Agent Architects

Agent Orchestration

Agent Memory Patterns

Planning and Reflection

Evaluation Frameworks

Guardrails & Safety

LangGraph

LangChain

Bedrock / OpenAI

RAG Architectures

Vector DB (Chroma / Weaviate)

Tools

LangGraph

LangChain

Google ADK

MCP (Model Context Protocol)

A2A Protocol

Tool Calling Frameworks

Bedrock / Azure OpenAI

Chroma

Weaviate

Job description

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.