Production search, recommendation, agentic, and developer platforms—owned from architecture through adoption, reliability, and measurable commercial impact.
Each system pairs a real operating problem with deliberate engineering choices and a measurable result.
Designed a context-aware multilingual retrieval system for fragmented enterprise knowledge across four languages.
Built data-driven personalization capabilities to improve healthcare-professional engagement and retention.
Standardized the foundations for RAG and agentic use cases so teams could ship on shared patterns instead of rebuilding core infrastructure.
Reworked CI/CD and cloud architecture to reduce release latency, improve operating efficiency, and lower recurring infrastructure cost.
The work spans architecture, hands-on engineering, product judgment, and business ownership.
Retrieval, ranking, recommendations, RAG, agents, and evaluation.
Cloud architecture, CI/CD, infrastructure automation, and observability.
Problem framing, prioritization, adoption, experimentation, and roadmap trade-offs.
Retention, delivery velocity, cost structure, support performance, and market rollout.
A progression from business operations to full-stack systems, machine learning platforms, and enterprise AI leadership.
Biomedical engineering, systems, and analytics.