at Capgemini
ConsultanciesPosted 13 days ago
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**AI Architect-D** leads Agentic AI development by leveraging Multi-Agent Architectures, Agentic Workflows, Agent Orchestration, and Memory Patterns. Hands-on experience with LangGraph, LangChain, Google ADK, MCP, and A2A Protocol is essential. Candidates must have Bedrock-hosted models or Azure OpenAI experience, plus expertise in RAG architectures, vector databases (Chroma, Weaviate) and embeddings, semantic search, planning and reflection frameworks, and AI governance. Proven track record in building scalable AI platforms, integrating with business applications, and adhering to security controls.
- Compensation
- Not specified
- City
- Not specified
- Country
- India
Currency: Not specified
Full 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.
