Engage on end-to-end delivery or focused engagements — I plug into founder-led teams and enterprises seeking pragmatic AI adoption and production-grade backend systems.
LLM integration, document AI parsing, semantic matching, conversational workflows, and realtime AI voice/interview systems.
Service-oriented backends with clean REST APIs, domain services, and asynchronous workers.
Full-stack AWS experience — serverless and traditional server-based — architected per workload, not serverless by default.
Data modeling and vector search for AI-driven matching and retrieval across relational and NoSQL stores.
Reliability patterns and CI/CD so systems stay observable, cost-aware, and resilient in production.
Access control and privacy-first data handling designed in from day one, not bolted on later.
I work across architecture, backend development, cloud infrastructure, and AI engineering with a focus on clear decisions, rapid iteration, and reliable production systems.
Understand the product, requirements, existing systems, and constraints. Define the technical scope, architecture, integrations, and delivery plan.
Build the core backend, APIs, AI workflows, and infrastructure. Ship an initial working version quickly, validate assumptions, and iterate based on real feedback.
Harden infrastructure, automate deployments, improve reliability, and optimize systems for security, performance, and cost as the product grows.