Experience & Background
I am a Sr. Software Engineer with 4+ years of experience architecting resilient distributed systems, enterprise commerce backends, and production AI agent workflows. My engineering focus centers on deep Medusa.js customization (authoring open-source npm plugins, media adapters, fulfillment providers, payment gateways, and ERP synchronization modules), high-scale database performance engineering (reducing complex PostgreSQL queries across 200,000+ SKUs from ~40s to <6s with Redis caching), and autonomous LLM orchestration using Python and FastAPI. I champion Clean Architecture, SOLID principles, zero-downtime releases, and developer mentorship — aligning engineering excellence directly with measurable business velocity and high-concurrency production reliability.
Skills
Skills & Toolkit
Core engineering toolkit & architectural competencies:
- Architect, develop, and operate high-throughput distributed backend services, asynchronous event queues, and REST/GraphQL APIs using Node.js, TypeScript, Python, FastAPI, Next.js, PostgreSQL, Redis, and Docker.
- Lead cross-functional engineering teams through technical RFCs, sprint planning, accurate estimation, pull request reviews, and developer mentorship, establishing engineering best practices across the organization.
- Engineered database query optimizations and caching architectures (PostgreSQL indexing, query plan profiling with EXPLAIN ANALYZE, and Redis multi-tier caching), slashing query latency by 85% on 200,000+ SKUs.
- Architected end-to-end multi-agent AI platforms with FastAPI, Celery, and LLM tool-calling integrations, automating resume parsing, semantic matching, and dynamic candidate interview evaluations.
- Built modular enterprise headless commerce systems (Medusa.js / Payload CMS / Next.js) featuring custom dynamic pricing engines, multi-tier inventory synchronization, and zero-downtime deployments.
- Enforced Clean Architecture, SOLID principles, OAuth 2.0/JWT security, fine-grained RBAC, and containerized CI/CD automation across production cloud environments on AWS.