Senior Backend Engineer building reliable, production-grade systems across distributed systems, data-intensive services, and AI applications.

I enjoy turning ambiguous production problems into clearly scoped projects, making difficult technical trade-offs explicit, and carrying systems from design through operation.

• Backend systems with Rust, Go, Python, PostgreSQL, Redis, and Kafka
• Distributed systems, reliability, idempotency, and failure handling
• High-throughput services and inventory/order workflows
• Embedding retrieval, evaluation, and model-drift detection
• LLM application architecture and production AI systems
• AWS, Kubernetes, Docker, and infrastructure automation
• Observability, incident response, and operational tooling

• Start with the actual problem, not the technology.
• Make trade-offs explicit, especially when reliability, cost, and throughput conflict.
• Prefer incremental designs that teams can adopt and operate.
• Treat evaluation and monitoring as part of the system, not an afterthought.
• Optimize for systems that remain understandable under failure.
• Good engineering includes knowing what not to build.

I've worked on systems involving:

• High-volume transaction processing and write-path consistency
• Duplicate detection across millions of records using vector retrieval
• Reservation and reconciliation systems for high-traffic workloads
• Production ML/LLM evaluation and model-drift detection
• Reliability improvements driven by real production failures
• Cross-team technical design and API/interface contracts

Distributed systems, backend architecture, AI infrastructure, LLM applications, developer tooling, and the engineering problems that appear when software has to work reliably at scale.

If you're working on an interesting systems or AI problem, feel free to reach out.