• Deploy and manage scalable containerized applications on GCP, leveraging GCS buckets for structured and unstructured data storage across services.
• Built backend-centric Next.js services using SSR and API routes, integrating SQL and BigQuery to process large-scale datasets and improve API response latency by ~30%.
• Containerized applications with Docker, enabling consistent deployments and smoother release workflows across environments.

• Completed 8+ weeks of structured Core Java training, applying OOP, collections, and exception handling in 2+ mini-projects.
• Designed CI/CD pipelines using Git, Jenkins, and Docker, automating build and deployment for 3+ services and integrating Java, Python, and DevOps tools.

Python, FastAPI, TimescaleDB, PostgreSQL, Redis, Celery, React, TypeScript, MapLibre GL, Docker, Vercel, Cloudflare

• Architected a production-grade maritime intelligence platform ingesting live global AIS feeds, tracking 1,600+ active vessels in real time and streaming position updates to an interactive world map via WebSocket — achieving sub-second latency across simultaneous connections.
• Designed a composite risk scoring engine (ETA deviation × port congestion × live weather hazards) running on a Celery Beat scheduler every 10 minutes, automatically classifying shipments as LOW / MEDIUM / HIGH risk and dispatching alerts to Slack and email with a configurable cooldown — reducing manual monitoring overhead to zero.
• Modeled a TimescaleDB time-series schema with hypertables, spatial indexes (PostGIS), and continuous aggregates for vessel positions and port congestion, enabling sub-100ms analytical queries over millions of rows without full table scans.
• Deployed a containerized 8-service stack (FastAPI, Celery worker + beat, AIS consumer, vessel simulator, Redis, TimescaleDB, React frontend) using Docker Compose; served the frontend on Vercel and exposed the local API globally via Cloudflare Tunnel — full production setup with zero cloud server cost.

Python, Streamlit, LangChain, Groq API, LLaMA 3.3-70B, ChromaDB, BeautifulSoup4, Pandas

• Built an AI-powered cold email generator using Python, LangChain, and Streamlit that automates personalized outreach for business development.
• Integrated Groq API with Meta's LLaMA 3.3-70B model to extract structured job data (role, skills, experience) from scraped career pages using prompt engineering.
• Implemented a ChromaDB vector store to semantically match job-required skills against a portfolio of 20+ tech-stack/project-link pairs using similarity search.
• Developed a web scraping pipeline with LangChain's WebBaseLoader and regex-based text cleaning to parse any job posting URL.
• Chained multiple LangChain PromptTemplates to build a two-step RAG pipeline: job extraction → context-aware email generation with relevant portfolio links.
• Deployed an interactive Streamlit web UI enabling one-click cold email generation from any job URL.

Next.js 15, TypeScript, Tailwind CSS, Notion API, Framer Motion, Resend, Vercel

• Built a full-stack personal portfolio using Next.js 15 App Router with TypeScript and Tailwind CSS, deployed on Vercel with ISR (revalidate=3600) and an on-demand revalidation webhook for near-instant content updates.
• Integrated Notion as a headless CMS for the blog — converts Notion blocks to Markdown via notion-to-md, renders with react-markdown + rehype-highlight for full syntax-highlighted code blocks.
• Wired live GitHub API and GeeksforGeeks API integrations to surface real-time coding stats (repos, stars, followers, DSA problem breakdown by difficulty) using parallel server-side fetches.
• Implemented UX details including Framer Motion page transitions, an IntersectionObserver-based sticky table of contents with active-heading tracking, and a scroll-driven reading progress bar.
• Built a contact form backed by the Resend email API with client-side loading/success/error states, and a /api/revalidate webhook route for Notion-triggered cache purges.