• About Me
• Highlights
• Skill Set
  • Languages & Runtime
  • Frontend
  • Backend & APIs
  • Databases & Data
  • Cloud, DevOps & Observability
  • Testing & Quality
  • Artificial Intelligence & Machine Learning
  • Mobile & Multiplatform
• Modern Full‑Stack Frameworks & Stacks
• Featured Tech Stack Playbooks
• Architecture Overview

🔭 I design and ship production‑ready web platforms with modern DX, performance, and accessibility at the core. 🤖 I specialize in integrating LLMs, RAG, and automation into real products—safely and observably. 🧩 I bridge frontend, backend, data, and DevOps to deliver cohesive, measurable outcomes. 🤝 Open to AI‑powered SaaS, platform engineering, and OSS collaboration.

• 🚀 End‑to‑end delivery: from idea to production with measurable outcomes
• 🧠 AI‑augmented apps: LLMs, RAG, prompt telemetry, safety guardrails
• ⚡ Performance‑first: edge rendering, caching strategy, profiling & budgets
• 🔒 Secure by default: authN/Z, secrets, threat‑modeling, least‑privilege IaC
• 🔁 DevEx & speed: monorepos, codegen, CI/CD previews, trunk‑based flow

What I deliver ✅ Production‑grade full‑stack apps (edge‑ready, SSR/ISR, server actions) ✅ RAG‑enabled features (secure retrieval, evals, guardrails) ✅ CI/CD with preview deployments and feature environments ✅ Observability (traces, logs, APM) and performance budgets

• Frontend: Next.js App Router (SSR/ISR, Server Actions), Tailwind CSS, TanStack Query
• API: tRPC or GraphQL, Zod validation, Server Components
• Data: PostgreSQL (Prisma), Redis (rate limiting, cache), S3/Cloudflare R2
• Auth & Payments: Auth.js/Clerk, Stripe, Webhooks (svix)
• DevOps: Vercel (Preview envs), GitHub Actions, Sentry + OpenTelemetry

• Inference: OpenAI/Anthropic, Vercel AI SDK or LangChain
• Retrieval: Pinecone or FAISS, hybrid search (Elasticsearch), chunking + embeddings
• Orchestration: Background jobs (BullMQ/Temporal), observability traces for prompts
• Safety/Evals: Guardrails, prompt/response logging, offline evals

• Backend: NestJS (WebSockets), Kafka/NATS for event streaming, CQRS where useful
• State: Redis pub/sub, Postgres logical replication for read models
• UI: React/Next.js + Presence/CRDTs as needed (yjs/automerge)

• Web: Remix or Next.js, SEO‑first routing, edge caching
• Commerce: Stripe/Shopify Storefront API, Medusa (headless)
• Content: Sanity/Contentful, image pipelines (Cloudflare Images/Vercel OG)

• Services: FastAPI/Django, Celery/RQ workers
• Storage: Postgres, ClickHouse (analytics), Lake (S3/R2)
• Pipeline: Airflow/Prefect, dbt, ELT into warehouse + semantic layer

• Expo + React Native, tRPC/GraphQL to backend, OTA updates (EAS)

graph LR
  A["Client Apps\nWeb · Mobile"] --> B["Edge Layer\nCDN · WAF · Functions"]
  B --> C["Web Server\nNext.js · Remix"]
  B --> D["API Layer\nNestJS · FastAPI"]
  C --> D
  D --> E["Workers & Queues\nBullMQ · Temporal"]
  D --> F["Databases\nPostgres · MongoDB"]
  D --> G["Caches\nRedis"]
  D --> H["Vector Store\nPinecone · FAISS"]
  D --> I["Search\nElasticsearch"]
  D --> J["Object Storage\nS3 · R2"]
  D --> K["Observability\nOpenTelemetry → Sentry/Datadog"]

If you’re building something interesting (SaaS, AI features, platforms), I’d love to collaborate. Reach out via GitHub.