Projects

GitHub Live App

AI / Full Stack

Inferr

01
  • Built a full-stack AI developer news platform in a pnpm + Turborepo monorepo (Next.js 15 frontend + NestJS 11 API) with Drizzle ORM, deployed on Vercel (web) and Render (API) backed by Neon PostgreSQL + pgvector.
  • Engineered a 10-source daily ingestion pipeline (Hacker News, Dev.to, Reddit /r/programming & /r/webdev, Lobste.rs, Hashnode, Medium, TechCrunch, GitHub, HackerNoon) driven by user interest tags: parallel metadata fetch → concurrent Cheerio content scraping (batches of 5, 8k char cap) → gpt-4o-mini summarization + text-embedding-3-small embeddings. Idempotent via URL deduplication, 24h freshness filter, and tag-aware balancing.
  • Designed a production-grade personalized feed using cached per-user query embeddings: pgvector cosine ANN + dynamic tag-overlap bonus (+0.15 per match, max +0.3), strict relevance threshold (distance < 0.5), 1-day recency, and source-diversity selection logic that returns the highest-ranked article per source before filling remaining slots (top 5–6).
  • Implemented a LangGraph agentic RAG pipeline (retrieve → grade → rewrite → generate) accepting multi-turn history. Uses k=6 retrieval, structured LLM grader (Zod), query rewriting up to 2 iterations when no documents pass grading, and strict separation of originalQuestion vs. searchQuery. Integrated Langfuse tracing + fire-and-forget faithfulness/relevance/recall evaluations persisted to ai_evaluations.
  • Built a complete MCP server (Streamable HTTP transport) exposing 5 user-scoped tools: search_articles, get_personalized_feed, ask_inferr (full agentic flow), get_market_report, and get_job_report. Implemented a full OAuth 2.1 + PKCE authorization server (delegated Google sign-in) with dedicated tables (mcp_clients, pending_mcp_authorizations, pending_auth_codes, mcp_tokens), SHA-256 refresh token rotation, replay detection that revokes the full token chain, and type-scoped JWTs ('mcp_access') separate from web sessions.
  • Implemented dual secure auth systems: web uses 15-minute JWT access + 7-day HttpOnly refresh tokens with atomic replacement-chain traversal in Drizzle; MCP uses 1-hour access + 7-day refresh optimized for machine clients.
  • Delivered a live Tech Market feature: Remotive jobs scraper + two GPT-4o-mini generated reports (demand signals + hiring stats) cached in Postgres (market_reports + jobs) with 24h TTL and in-flight request coalescing.
  • Authored a complete Kubernetes deployment suite (StatefulSet for pgvector Postgres with PVC, Redis Deployment, API Deployment with initContainer wait-for-db + liveness/readiness probes, Services, nginx Ingress, and CronJob for nightly scraper runs) alongside the Render + Vercel cloud path.
  • Added full observability: OpenTelemetry auto-instrumentation (traces to Jaeger) and Langfuse for every LLM and agent step.
Next.js 15NestJS 11TypeScriptDrizzle ORMpgvectorLangGraphOpenAIMCP SDKOAuth 2.1LangfuseKubernetes
GitHub

Backend

DevNest

02
  • Built a modular NestJS backend for a social platform with dedicated auth, posts, comments, likes, feed, profile, email, and shared infrastructure layers backed by PostgreSQL as the system of record.
  • Implemented secure authentication with JWT access tokens, HTTP-only refresh token rotation, session caps, token reuse detection, soft-delete account revocation, Google OAuth 2.0 sign-in, and SHA-256 hashing of stored login IP metadata.
  • Designed pull-based public and follower feed APIs with cursor pagination, Redis-backed caching, and Prisma query patterns that return author metadata and interaction counts without feed fan-out duplication.
  • Engineered Redis-backed platform infrastructure for distributed rate limiting, cacheable profile and content reads, and BullMQ worker processing for asynchronous welcome email jobs.
  • Offloaded CPU-heavy bcrypt hashing and password verification to a piscina worker-thread pool to keep request handling responsive under concurrent authentication load.
  • Validated production-critical behavior through Jest E2E coverage for auth, posts, comments, likes, feeds, rate limiting, cursor pagination, soft-delete flows, and worker-pool concurrency.
TypeScriptNestJSPostgreSQLRedisPrismaBullMQPiscina (Workers)Jest E2E
GitHub

AI / RAG

PG RAG

03
  • Architected a complete RAG (Retrieval-Augmented Generation) pipeline using LlamaIndex to orchestrate document ingestion, vector indexing, and LLM generation.
  • Implemented an Intelligence Layer for query rewriting and intent detection, allowing the system to handle complex multi-turn conversations and clarify user intent.
  • Engineered a high-performance vector retrieval system using FAISS and HuggingFace embeddings for sub-50ms semantic search across thousands of text chunks.
  • Developed a responsive Next.js 16 frontend with real-time streaming (NDJSON) and a minimalist, glassmorphic UI providing a premium ChatGPT-like experience.
  • Orchestrated local and cloud LLMs (Ollama, OpenAI) via a FastAPI backend, handling asynchronous event streams for low-latency interactions.
LlamaIndexFastAPIFAISSPythonOllamaNext.js 16Tailwind CSS 4