Roles & Responsibilities:

· Define and own end-to-end GenAI architecture, including LLM orchestration, agent frameworks, and enterprise integrations.

· Design scalable, modular solutions using LLMs, embeddings, vector databases, and retrieval mechanisms.

· Architect agent-based and multi-agent systems for autonomous reasoning, planning, and workflow execution.

· Establish GenAI design patterns such as RAG, conversational AI, document intelligence, and context-aware systems.

· Lead integration of GenAI solutions with enterprise systems using APIs, microservices, and event-driven architectures.

· Define prompt engineering strategies, prompt lifecycle management, and context orchestration frameworks.

· Implement Responsible AI practices including governance, explainability, security, and compliance.

· Design human-in-the-loop architectures with feedback loops, validation checkpoints, and fallback mechanisms.

· Establish monitoring and observability for model accuracy, hallucination detection, drift, and cost optimization.

· Collaborate with business stakeholders to identify high-impact AI use cases and define transformation roadmaps.

· Standardize GenAI architecture practices, reusable components, and governance policies.

· Mentor engineering teams on GenAI, LLMOps, and AI-first solution design