Designs and operates cloud infrastructure and enterprise AI systems, including service integrations, reusable infrastructure-as-code modules, automation frameworks, policy controls, observability, and AI workflow guardrails. Leads incident resolution, architectural improvements, capacity and cost planning, SaaS integrations, and operational process optimization. Creates technical documentation and engineering standards while mentoring engineers and driving adoption of scalable AI and automation practices across teams.

Design, build, and operate low-latency, cloud-native AI-powered fraud decisioning and automated remediation systems. Implement AI-assisted SDLC and agentic multi-agent workflows, modernize streaming/data pipelines and microservices, ensure observability/SLOs/security, evaluate vendor solutions, and mentor engineers.