Agentic AI Architect

Agentic AI Architect (8-12 yrs) Role Summary: We are looking for a Senior Agentic AI Architect to design and build a next-generation enterprise Agentic AI platform and solutions powering hundreds of users and complex multi-agent workflows.This role goes beyond LLM integration—you will define agentic architecture, orchestration patterns, governance frameworks, and enterprise-scale deployment strategies to enable autonomous, reliable, and explainable AI systems.You will work closely with product, engineering, and business stakeholders to transform AI from experimentation to production-grade, business-critical systems. Responsibilities Define end-to-end architecture for multi-agent systems (hierarchical, collaborative, autonomous agents) Design reusable agent frameworks, templates, and SDKs Establish agent orchestration patterns (planner-executor, tool-using agents, multi-agent coordination) Design agent control planes (task routing, agent selection, execution flows) Define patterns for: Human-in-the-loop, Agent supervision & escalation, Multi-agent negotiation & collaboration Build and deploy frameworks for Agent governance & policy enforcement Define metrics for:Agent accuracy, latency, cost, and success rate Design Context window optimization strategies, Dynamic context injection, Memory pruning & summarization Define agent interaction paradigms:Conversational UX, Task-driven workflows Evaluate and leverage platforms like Azure AI Foundry / AWS Bedrock / Google Vertex AI/Langgraph Skills & Qualifications : Strong expertise in Generative AI, LLMs, and Agentic AI systems Hands-on experience with agent frameworks (Microsoft Foundry agent, CrewAI, Google ADK, Langgraph) Deep understanding of multi-agent architectures and orchestration patterns Proficiency in Python and/or TypeScript for AI system development Experience with cloud platforms (Azure, AWS, or Google Cloud) and AI services Knowledge of RAG, vector databases, and context engineering techniques Experience designing scalable, distributed, and microservices-based architectures Strong understanding of AI governance, guardrails, and responsible AI practices Experience with model evaluation, performance optimization, and monitoring Ability to translate business requirements into enterprise-grade AI solutions