Vetted Database Schema Design Professionals

Niyaz Herkal

Screened

Mid Backend Engineer specializing in scalable APIs and cloud microservices

Bangalore, India3y exp

“Backend-heavy full-stack engineer who owned a high-volume booking/rescheduling system at CodeHaste, using NestJS, PostgreSQL, and advanced TypeScript patterns to eliminate double-booking issues at 10k+ daily transactions. Also co-founded KingpiN Vision Forge, where they turn ambiguous client asks into concrete web strategy and design, and has adjacent AI infrastructure experience integrating NVIDIA NIM APIs and debugging streaming issues.”

Gabe Hoing

Screened

Intern-level software engineer specializing in full-stack and data systems

Spokane, WA2y exp

“Built an AI agent management system in a senior design project to support cybersecurity analysts with gathering and triaging emerging threat intelligence from sources like CISA. Stands out for a thoughtful, production-minded approach to AI development, using specialized agents, strict output schemas, and deterministic controls to manage failure cases.”

Uvesh Chauhan

Screened ReferencesStrong rec.

Mid-level Full-Stack Developer specializing in AI and cybersecurity platforms

New Delhi, India6y exp

“Builder of multiple AI products including Nova-Core, a multi-model assistant using Grok and Gemini, and Lumina Shield, a prototype for vulnerability detection and performance analysis that routes findings into Nova-Core for explanation and fixes. Also created a desktop voice agent ('Soul') and brings 6 years of experience in a non-profit audio consultancy, with a personal story of being a cancer survivor motivated by purpose-driven work.”

Akash Parekh

Screened

Mid-level Full-Stack Developer specializing in React, Node.js, and cloud deployment

Toronto, Canada3y exp

“Frontend engineer with experience building enterprise ERP/CRM dashboards in React + TypeScript, including cron-driven data updates and differentiated state flows. Emphasizes CI/CD pipeline setup, performance optimization (Core Web Vitals, React Profiler), and disciplined delivery practices (risk-based QA, phased rollouts); also has Figma-to-responsive implementation experience.”

“Front-end engineer focused on sophisticated browser-based search and reading experiences, including AI-generated summaries and multi-state content interfaces. Demonstrates strong practical skill in React-style component architecture, Figma-accurate implementation, and deep browser/CSS debugging to make complex UIs polished, maintainable, and usable.”

Donovan Kelley

Screened

Senior stage technician specializing in live event production and entertainment technology

San Francisco, CA13y exp

“New December 2025 graduate with primarily academic experience who is already building a real-world Flask application for their current job. Created a technician availability system used across four unions and about 150 technicians, with SQLite, Jinja, Bootstrap, Auth0, PythonAnywhere, and Cloudflare.”

Hitha Sunkara

Screened

Junior Full-Stack Developer specializing in web apps and machine learning

Long Beach, CA3y exp

“Built and organized SQL databases for a grocery pricing update backend and has hands-on experience designing FastAPI/Python APIs with security controls like authentication, RBAC, and strict validation. Also brings research experience identifying real-world failure modes (weather-driven sensor/model inaccuracies in MSE wall corrosion work) and adapting models to improve robustness, plus UI design support on an email-restricted campus hackathon enrollment flow.”

“Full-stack developer with TypeScript/Next.js and Python/FastAPI experience who has shipped production features and owned them through deployment issues. Particularly interesting for data-heavy or compute-intensive products: they worked on a cilantro yield estimation system using PostgreSQL/Supabase, Gaussian Splatting, and Modal-based serverless GPU processing to improve parallel job throughput and delivery speed.”

“Built and shipped a production LLM-powered document processing agent (ingestion→OCR→LLM extraction/classification→validation→DB/workflow triggers) using Kafka and PostgreSQL. Emphasizes production reliability with strict JSON schemas, idempotent services, retries/backoff, fallback models, and human-in-the-loop review—driving ~90% automation, minutes-to-seconds processing, and ~10x throughput.”