Vetted Supabase Professionals

“Built and owned the core execution pipeline for Drona, an AI code grading platform, spanning Next.js frontend, real-time WebSocket updates, Celery/Redis async processing, Docker sandboxing, and PostgreSQL persistence. Particularly strong in backend reliability and architecture, with concrete wins including reducing API response time from about 5 seconds to 200 ms and eliminating silent job failures in production.”

“Built a university campus assistant chatbot (BabyJ/WWJ) using RAG and agentic routing with a FastAPI + React stack and JWT auth, focusing heavily on production concerns like latency and reliability. Uses techniques like speculative prefetching, smart intent routing, and rigorous eval/testing (golden sets, regression, edge cases) while collaborating closely with campus admin/advising teams to iterate based on real user feedback.”

Ayushant Khandekar

Screened

Junior Full-Stack Developer specializing in GenAI-powered web and mobile apps

Remote2y exp

“Web3 creator-led growth and community builder who frames crypto as infrastructure and designs content to drive measurable on-chain behavior. Uses X-native distribution (threads, replies, quote-tweets) paired with interactive CTAs and on-chain dashboards to convert attention into trust and product usage, with a structured 90-day plan for launching and scaling protocol communities.”

“Frontend/full-stack engineer with startup experience who described building a HIPAA-compliant telehealth and e-commerce platform from scratch using Next.js and TypeScript. Stands out for combining security-conscious browser architecture, real-time data handling, and performance optimization, including a reported 51% UX improvement and shipping an MVP two weeks early.”

“Backend/ML engineering candidate focused on fintech automation who architected a zero-to-one agentic/LLM-enabled system to reconcile messy financial documents and bank transactions, reporting ~40% operational efficiency gains. Experienced migrating monoliths to event-driven microservices with incremental rollout via reverse proxy, and implementing production-grade security (OAuth2/JWT, RBAC, Supabase RLS) plus resilience patterns (timeouts/retries under concurrency).”

“Backend engineer who built and scaled a FastAPI-based backend for an AI-driven maintenance system automating vendor sourcing/bidding/communication. Emphasizes async, message-driven architecture with strong observability and state-machine-driven workflows, plus robust webhook/idempotency patterns to prevent duplicate/out-of-order events from causing bad bids or state changes.”

Lalith Sagar Kambala

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Junior Full-Stack Software Engineer specializing in AI-powered SaaS

United States, USA1y exp

“Worked on an AI-adjacent search/results product with a React front end and an API-driven backend, focusing on scalability and performance. Emphasizes decoupled JSON API architecture, React rendering optimizations (useMemo/useCallback), and large-dataset techniques like virtualization, plus strong user-issue triage via log analysis and edge-case fixes in query handling/ranking.”

Ibrahim Cheena

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Junior Software Engineer specializing in distributed systems and AI platforms

San Jose, CA3y exp

“Built ContextIQ, an end-to-end full-stack RAG document assistant using Next.js, TypeScript, OpenAI embeddings, Supabase/pgvector, and streaming responses to create a real-time research experience. Also built DevWatch, a GitHub analytics and QA dashboard with Java Spring Boot and PostgreSQL, and demonstrated strong production ownership by solving cloud networking, cold start, CORS, and data deduplication issues after launch.”

John Kenny

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Senior Full-Stack Engineer specializing in Web3 and FinTech

Global, Remote6y exp

“Full-stack engineer with deep startup experience (pre-seed through IPO/SPAC) currently building a Next.js/TypeScript SaaS sports analytics platform with a complex Postgres-based entitlement/ACL system. Has delivered measurable UX/business impact (35% retention lift, 40% volume increase) and built production-grade daily ETL + model training/inference workflows with validation and checkpointing for reliability.”