ENGINEER / ARCHITECT OF SYSTEMS / APPLIED AI
AVAILABLE WORLDWIDE
I MAKE SYSTEMS BEHAVE.
<Try to Inspect Me>
I build secure production systems for high-volume workloads, refining how code executes, services communicate, data moves, and infrastructure scales, so the complexity underneath feels effortless on the surface.
I also build for the problems that appear next, turning new operational, security, and governance challenges into reusable systems that help teams respond faster and avoid solving the same problem twice.
Work across agentic systems, distributed data platforms, AI evaluation pipelines, and internal engineering platforms—designed for scale, reliability, and developer leverage.
Reduced inventory-consumption prediction from ~25 days to 1.5 days by redesigning queries, optimizing service calls, fixing algorithmic bottlenecks, eliminating redundant processing, and right-sizing database and pod usage for high-volume workloads, cutting processing time by roughly 94%.
Scaled the same workload window from ~300K to 3M+ queries while reducing ~20% timeouts to near zero through bounded concurrency, backpressure, Pub/Sub optimization, retry tuning, and workload alignment with database capacity, delivering 10× throughput with near-zero failures.
Turned complex E2E testing into reusable, composable workflows across Pub/Sub, APIs, databases, BigQuery, and bucket operations, runnable on demand, automated in CI, and assembled by agents from reusable building blocks, improving developer quality of life at scale.
Scaled evaluation from sequential, single-application runs to thousands of multi-turn agent scenarios processed in parallel across autoscaling Dataflow workers, supported by golden datasets, multi-metric scoring, experiment tracking, regression gates, and CI integration, achieving enterprise-wide adoption.
MOVE THROUGH THE SYSTEM
What looks effortless on the surface is held together by the systems underneath.
