Built an end-to-end workflow with React/TypeScript UI and Python FastAPI services, reducing a 20–30 minute manual process to 2–3 minutes by streamlining UI steps and backend automation.

Designed versioned REST APIs in FastAPI with Pydantic schema validation and consistent error responses, reducing user-reported issues by 20% through tighter edge-case handling.

Implemented retrieval-backed generation using embeddings + vector search and structured JSON outputs, making results reliably renderable in the UI and improving engagement by 40%.

Built a grounded agent workflow with LangChain/LangGraph that composes user context and tool outputs with safe fallbacks, increasing automated task success by 35%.

Improved production reliability with Docker and CI/CD (GitHub Actions/Jenkins) plus integration tests and release checks, reducing production issues by 85% and improving release cadence by 30%.

Ran stakeholder demos and walkthroughs, wrote API and workflow documentation, and translated feedback into weekly releases and fixes.

Built an LLM-powered review application (Flask/FastAPI + React) → reduced manual workload 60%.

Created embeddings-based search, filtering, and UI components → improved exploration speed 30%.

Optimized BigQuery pipelines → increased ETL throughput 30%.

Strengthened LLM output quality through evaluation datasets, prompt experiments, and failure analysis.

Improved API latency 30% by optimizing Java Spring Boot microservices and distributed calls.

Boosted React/TypeScript UI performance 40% through caching, batching, and component tuning.

Increased MySQL performance 35% using indexing, schema refinement, and query optimization.

Built and maintained a portal serving 3,500+ users; reduced page load time by 30% via indexing and streamlining.

Automated administrative workflows (Python + JavaScript), cutting manual effort by 25%