What I built
- Built production LLM features on Node.js / NestJS: intent-based product search with parallel tool calling, multi-turn conversations, and post-search LLM ranking.
- Worked hands-on with OpenAI and Google Gemini models — prompt engineering, model selection, and structured outputs across search, ranking, and generation features.
- Implemented RAG retrieval over Elasticsearch + PostgreSQL with Redis caching, plus data-enrichment pipelines on AWS (SQS queues, Lambda functions) feeding the search index.
- Built eval cases and harnesses so search and ranking quality stays measurable across every model and prompt change.
- Delivered image / mockup generation and agentic workflows; profiled and optimized heap and request-path performance.
Stack & focus
Node.jsNestJSReactTypeScriptPostgreSQLElasticsearchRedisAWS LambdaSQSOpenAIGeminiRAGTool callingPrompt engineeringEvals & harnessesImage & mockup generationData enrichmentPerformance profiling