Design, develop, and deploy enterprise-grade autonomous AI services and multi-agent workflows. Build MCP and A2A integrations, hybrid control flows, secure tool execution environments, and reliable microservices. Apply SRE practices including fallbacks, circuit breakers, audit trails, and observability. Collaborate cross-functionally to translate business requirements into scalable agent specifications and production systems using Python, cloud foundation models, containerization, CI/CD, and distributed technologies.

Lead and grow an Agentic AI engineering team to transition multi-agent and generative AI POCs into scalable, secure, production-grade LLM services. Define technical roadmap, ensure architectures support hybrid control flows and state machines, adopt agent interoperability standards, establish CI/CD and observability, and partner with product and business leaders to deliver measurable business impact.