Principal engineer building AI-first platform capabilities, including agents, skills, context-driven workflows, and MCP-based integrations. Focused on designing scalable platform architecture, reusable backend services, and intelligent systems that enable automation, reliability, and adoption across teams. Experienced in distributed systems, platform strategy, and technical leadership at scale.

Principal-level technical leader driving cloud, AI, and platform architecture initiatives with measurable outcomes.

* Modernized legacy platforms into cloud-native microservices and event-driven systems; standardized infrastructure automation and container orchestration.

* Delivered AI-powered solutions that improved customer experience and reduced turnaround times.

* Designed automation pipelines cutting manual effort by ~70% and saving over $5M annually.

* Optimized cost, reliability, and observability, lowering infrastructure spend while improving uptime and performance.

* Defined scalable API patterns and CI/CD pipelines with secure, automated delivery.

* Established technical governance for architecture reviews, reliability, and compliance.

Recognition: Best AI Automation Architecture (Google NYC + Optum Hackathon).

Tech stack: Cloud platforms, Kubernetes, Terraform, Python, Java, messaging systems, relational and NoSQL databases, monitoring and CI/CD tools, AI/LLM frameworks.