Selected work
A public summary of selected work areas. Confidential implementation details, customer-specific data, and internal architecture are intentionally omitted.
Architect for agentic data, workflow, governance, privacy, and trust initiatives. Work includes multi-agent runtime harnesses, human-in-the-loop interrupts, API gateways, tool catalogs, workflow execution layers, memory-aware orchestration, extraction services, and policy-aware coordination for regulated healthcare use cases.
Technical leadership across multimodal AI initiatives, unstructured-to-structured data extraction, inference systems, model-serving foundations, multimodal reasoning pipelines, and integration patterns across AWS AI services and enterprise AI workflows.
Work across inference platform modernization, model-serving architecture, accelerated inference, data collection and processing platforms, training-data governance, privacy frameworks, and production deployment patterns for AI services.
Cloud-scale control-plane and data-plane work across CloudFront and Amazon Global Accelerator, including configuration serving, propagation systems, high-availability architecture, policy-based distribution selection, and distributed systems reliability.
Earlier engineering work spans enterprise lifecycle management, ordering systems, transportation systems, legal systems, PII-sensitive applications, and product/platform modernization across large organizations.
Trust, policy, and oversight must be designed into AI platforms from the beginning.
Enterprise AI needs evaluation, monitoring, reliability, and recovery paths.
Autonomous systems in healthcare need human-in-the-loop design and clear escalation paths.