GPU Infrastructure
Observability and fault detection for distributed GPU environments powering AI workloads.
I design and build production systems for AI workloads — with a focus on GPU observability, distributed data processing, reliability, and high-scale cloud infrastructure.
My work sits at the intersection of distributed systems, GPU infrastructure, AI platforms, and reliability engineering.
Observability and fault detection for distributed GPU environments powering AI workloads.
High-scale systems designed around availability, capacity, concurrency, and operational simplicity.
Developer-facing AI platforms, agentic tooling, MCP integrations, and NL-to-SQL.
Building GPU compute observability for OCI AI infrastructure, processing telemetry through Apache Flink to detect actionable infrastructure faults and publishing events to Apache Kafka.
Tech lead for Secure Big Data Gateway, including architecture, production launch, capacity planning, canarying, observability, and cross-team reliability work.
Built distributed database infrastructure including multi-tenancy, automation, and cross-account VPC connectivity.
Built microservices and internal platforms for merchant and content systems.
Streaming observability pipeline for GPU clusters.
Fault-tolerant execution with retries, event-sourced durability, deterministic replay, and OpenTelemetry tracing.
PagedAttention-style allocator with copy-on-write, prefix sharing, eviction policies, and benchmarking.
M.S. in Computer Science · 2018–2019
B.E. in Information Technology · 2011–2015
Interested in distributed systems, AI infrastructure, GPU platforms, or reliability engineering? Reach out.