{"$schema":"https://schema.org/Person","generatedAt":"2026-10-02T05:04:24.086Z","source":"https://0xshiv.dev/api/profile","profile":{"name":"Shivansh Goel","headline":"Full Stack Developer & AI Developer","tagline":"Building AI products for the real world.","summary":"Full Stack Developer building AI-enabled web products with Next.js, Python, and cloud infrastructure. Professional experience is 17 months of full-stack product work; the AI work is self-directed and shipped — adaptive fitness, document-grounded assessments, and privacy-first SaaS, all live and inspectable.","roles":["Full Stack Developer","AI Developer"],"location":{"label":"India","country":"IN"},"email":"shivansh.goela12@gmail.com","availability":"Open to full-stack & AI product roles","resumeUrl":"/resumes/resume_ShivanshGoel_FullStack.pdf","website":"https://0xshiv.dev"},"stats":{"experienceYears":1.5,"liveProducts":6,"aiProducts":3,"openSourceProjects":4},"skills":["Artificial Intelligence","Applied Machine Learning","AI Product Development","JavaScript","TypeScript","React","Next.js","Node.js","Python","AWS"],"roles":[{"id":"full-stack","title":"Full Stack Developer","summary":"Full Stack Developer building production web applications end to end with React, Next.js, and Node.js on serverless infrastructure. This is the track my paid experience sits in: 17 months building client-facing React and Angular interfaces, Node.js REST APIs, and MySQL/MongoDB data layers, plus six self-directed products shipped and running in the open.","focus":["End-to-end feature delivery","Responsive UIs with React & Next.js","REST APIs & database-backed services","Deployment on edge and serverless platforms"],"skills":["React","Next.js","Node.js","TypeScript","Angular","Python","Supabase","MySQL","Cloudflare Workers"],"resumeUrl":"https://0xshiv.dev/resumes/resume_ShivanshGoel_FullStack.pdf","exploreUrl":"https://0xshiv.dev/?role=full-stack#roles"},{"id":"ai-ml","title":"AI Developer","summary":"AI Developer integrating LLMs into live web products — document-grounded retrieval, prompt design for structured output, and server-side model calls that keep API keys off the client. My AI work is self-directed rather than employed: three products in production, all Gemini-backed, with retrieval and caching decisions made under real latency and cost constraints.","focus":["Retrieval-augmented generation over user documents","Prompt design for schema-consistent output","Server-side model calls & API key handling","Cutting repeat inference cost with caching"],"skills":["Google Gemini","RAG","Embeddings","Prompt Engineering","Python","FastAPI","Redis","Next.js","Supabase"],"resumeUrl":"https://0xshiv.dev/resumes/resume_ShivanshGoel_AI_ML.pdf","exploreUrl":"https://0xshiv.dev/?role=ai-ml#roles"}],"capabilities":[{"iconKey":"frontend","title":"Frontend Development","description":"Accessible, responsive interfaces with clean component architecture and smooth, purposeful interactions.","skills":["React","Next.js","Angular","Tailwind CSS"]},{"iconKey":"backend","title":"Backend Development","description":"Secure, well-structured RESTful APIs and services built for reliability and maintainable growth.","skills":["Node.js","Python","REST APIs"]},{"iconKey":"data","title":"Databases & Cloud","description":"Efficient data modeling and query optimization, with cloud deployments that scale on demand.","skills":["MySQL","MongoDB","AWS"]},{"iconKey":"fullstack","title":"Full Stack Solutions","description":"End-to-end product delivery — from architecture and implementation through to deployment and iteration.","skills":["TypeScript","System Design","CI/CD"]}],"experience":[{"id":1,"role":"Full Stack Developer — Intern","company":"TedForge Solutions Pvt. Ltd.","period":"Dec 2023 – May 2025","description":"A 17-month internship — long enough to own features end to end rather than shadow them. Built client-facing React and Angular interfaces, developed Node.js REST APIs, and reworked MySQL and MongoDB queries to cut overhead on data-heavy screens.","stack":["React","Angular","Node.js","MySQL","MongoDB"]}],"projects":[{"title":"Ziplink","category":"URL Shortener · SaaS","outcome":"Turns long URLs into trackable, brand-ready links that are easier to distribute across campaigns. QR downloads and edge redirects shorten the path from share to destination, while analytics make each link measurable.","stack":["Next.js","Firebase","Edge Redirects"],"liveUrl":"https://ziplink.0xshiv.dev","sourceUrl":"https://github.com/Tech-aficionado/ZipLink---Open-Source"},{"title":"GhostRelay","category":"Privacy · SaaS","outcome":"Keeps a real inbox out of sign-up forms by routing messages through disposable aliases. If an alias attracts spam, it can be disabled without changing the primary address — giving users a practical containment layer.","stack":["Cloudflare Workers","D1","Next.js","React 19","Resend"],"liveUrl":"https://ghostrelay.me","sourceUrl":"https://github.com/Tech-aficionado/GhostRelay---Open-Source"},{"title":"FiTrack AI","category":"AI · Fitness","outcome":"Brings workout, nutrition, and recovery signals into one adaptive flow. AI-guided intensity, macro breakdowns, and fatigue-aware recommendations reduce the manual work of reconciling separate fitness trackers.","stack":["Next.js","Python","Google Gemini"],"liveUrl":"https://fittrack.0xshiv.dev/","sourceUrl":null},{"title":"Quizify","category":"AI · Education","outcome":"Turns a topic into a ready-to-run assessment in seconds, reducing manual question writing. Instant explanations and mastery tracking show learners what to review next, while classroom codes make sharing straightforward.","stack":["Next.js","Google Gemini","RAG","Redis"],"liveUrl":"https://quizify.0xshiv.dev","sourceUrl":null},{"title":"DareStake","category":"Accountability · PWA","outcome":"Puts a real cost behind a daily commitment: two people set dares for each other, and a missed deadline moves money to a shared jar instead of passing unnoticed. Deadlines resolve against a single fixed timezone so a late-night check-in lands on the day the user meant, and penalties are claimed in a transaction so the same miss can never be charged twice.","stack":["Next.js","TypeScript","Firestore","PWA","Vitest"],"liveUrl":"https://darestake.0xshiv.dev","sourceUrl":"https://github.com/Tech-aficionado/darestake"},{"title":"MoodRadio","category":"AI · Music","outcome":"Takes a sentence about how someone feels and returns music that matches it, instead of asking the listener to pick a genre first. The interface adopts the colour of the detected emotion so the mood is visible, not just inferred, and candidate tracks are scored against the listener's own YouTube library and recent plays so the same few artists stop resurfacing.","stack":["Next.js","TypeScript","Google Gemini","YouTube Data API","Firebase"],"liveUrl":"https://moodradio.0xshiv.dev","sourceUrl":"https://github.com/Tech-aficionado/MoodRadio"}],"social":[{"label":"GitHub","url":"https://github.com/Tech-aficionado"},{"label":"LinkedIn","url":"https://www.linkedin.com/in/shivansh-goel-5b2309174/"},{"label":"Instagram","url":"https://www.instagram.com/shivanxx.__/"},{"label":"Hashnode","url":"https://tech-aficionado.hashnode.dev"},{"label":"Dev.to","url":"https://dev.to/tech-aficionado"},{"label":"Website","url":"https://0xshiv.dev"}]}