Agentic AI Architect-D

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.