Job Description:

Role & Responsibilities:

- Lead evaluation, benchmarking, and implementation of scalable, secure, and compliant Agentic AI frameworks aligned with enterprise business use cases and organizational strategies.

- Drive technical standardization and maturity in Generative and Agentic AI development by creating reusable orchestration blueprints, prompt engineering guides, best practices, and integration patterns to ensure consistent delivery in complex programs.

- Define scalable multi-agent system design patterns including tool usage, memory management, task routing, agent communication, human-in-the-loop processes, and orchestration frameworks.

- Establish evaluation frameworks to assess Agentic AI solution performance, focusing on reasoning, tool reliability, task completion, hallucination mitigation, and autonomous decision quality for production readiness and continuous improvement.

- Design enterprise Retrieval-Augmented Generation (RAG) architectures optimizing retrieval processes, embeddings, chunking, and reranking aligned with business goals and data governance, while mentoring AI engineering teams and collaborating with stakeholders to translate objectives into AI roadmaps.

- Manage client engagements including discovery, demos, proposal development, and delivery planning, leveraging strong DevOps, LLMOps, containerization, and CI/CD pipeline expertise to ensure successful, trusted partnerships and stay updated on Agentic AI and Generative AI advancements.