Applied AI & Full-Stack AI builder focused on AI agent systems, LLM evaluation, Supabase-backed product architecture, and deployed MVPs.
India | Open to Remote Global Roles
I am a B.Tech Information Technology student, graduating in 2028, who builds Applied AI and Full-Stack AI projects. My strongest proof of work is EvalGate and AIMS, two deployed, Supabase-backed MVPs. I focus on evaluation and governance workflows, project-scoped data, Row Level Security, dashboards, and practical product implementation. I am targeting Applied AI, AI Agent Engineering, AI Evaluation, Full-Stack AI, and startup engineering opportunities.
A deterministic evaluation platform for testing prompt and AI-agent changes and turning persisted results into clear release decisions.
Technical highlights
- Reusable test case and prompt version registries
- Deterministic evaluation runner with category-aware and priority-aware scoring
- Ship, Needs Review, or Block release decisions
- Safety failure override, persisted evaluation runs and results, reports, and audit timeline
- Project/workspace scoping with Supabase Auth, Postgres, and Row Level Security
MVP boundary: EvalGate intentionally uses deterministic evaluation to demonstrate evaluation architecture, scoring, release gating, and product thinking. It does not call AI providers or use agent frameworks, RAG, embeddings, or vector databases.
A control plane for organizing AI-agent operations, governance records, execution evidence, risk monitoring, and audit activity.
Technical highlights
- Agent registry and tool governance
- Knowledge-source tracking and execution evidence
- Run monitoring, operational risk views, dashboard metrics, and audit timeline
- Safe error handling and project-scoped Supabase queries
- Project/workspace scoping with Supabase Auth, Postgres, and Row Level Security
MVP boundary: AIMS is a control plane, not an agent runtime. It does not execute agents, call AI providers, invoke tools automatically, or use RAG or embeddings.
- AI agent systems
- LLM evaluation and release readiness
- Prompt testing and deterministic scoring
- Supabase Auth, Postgres, and Row Level Security
- Next.js App Router and TypeScript
- Full-stack MVP implementation
- Product thinking and system design basics
- Languages: TypeScript, Python, C, C++, SQL basics
- Frontend: Next.js App Router, React, Tailwind CSS
- Backend / Database: Supabase Auth, Supabase Postgres, Row Level Security, PostgreSQL basics
- AI / LLM Systems: Prompt writing, AI engineering fundamentals, AI automation concepts, deterministic evaluation workflows
- Tools / Deployment: Vercel, GitHub, GitHub Codespaces, NotebookLM, Claude, ChatGPT, Codex-assisted development
I am open to Applied AI Engineer, AI Agent Engineer, AI Evaluation Engineer, Full-Stack AI, AI Product Engineer, Founding Engineer, and AI Implementation Engineer internships, as well as AI residency or accelerator programs. I am also interested in junior, apprentice, or contractor roles where my project experience is a strong fit.
Currently building and applying for Applied AI, AI Agent Engineering, and Full-Stack AI opportunities.
- Email: parthrebhe11@gmail.com
- LinkedIn: linkedin.com/in/parth-rebhe-805b82359
- GitHub: github.com/wdevelper11-cloud