Vetted OpenAI Professionals

“Full-stack developer who uses AI deliberately rather than blindly, keeping generated code to a minority of core feature work so they retain full understanding of data flow. Built a React/TypeScript + Supabase task management app and shows strong judgment around debugging hallucinated schema/query output, refactoring for maintainability, and prioritizing security and logic over boilerplate speed.”

“LLM/agentic AI builder who deployed a production ITSM automation agent on Google ADK integrating ServiceNow and FreshService, with strong safety guardrails (human-approval gating and runbook-only command execution) and rigorous evaluation (500 synthetic tickets; 80%+ false-positive reduction). Also partnered with finance to deliver an AI agent that automated invoice/SOW retrieval and monthly reporting to account managers, reducing manual back-and-forth.”

“Software engineer with enterprise CPQ/CRM/ERP integration experience (Argano) who owned an end-to-end pricing preview capability deployed on AWS Kubernetes with Jenkins CI/CD and full observability (Prometheus/Grafana). Also built an AI-native research agent using LangChain + Chroma to filter academic papers, reporting ~15 hours/week saved for a professor.”

“Independent builder of production-grade systems: shipped an end-to-end URL shortener with JWT auth, Redis rate limiting/caching, Postgres, Docker, and real-time analytics, and separately architected a Redis-backed distributed task queue handling 1000+ tasks/min. Demonstrates strong distributed-systems instincts (atomicity, retries/DLQ, idempotency, heartbeats) plus a focus on maintainable code and self-documenting APIs (FastAPI/OpenAPI, versioned routes).”

“Built GynAI, an end-to-end maternal clinical decision support platform for OB/GYN practices and hospitals in North America, combining predictive ML with RAG-based LLM explainability. The candidate emphasizes real production ownership across experimentation, deployment, monitoring, and iteration, with reported impact including fewer delayed interventions in high-risk pregnancies and a 15-20% reduction in false positives.”

Ratinder Joshi

Screened

Intern Full-Stack Software Engineer specializing in AI and SaaS platforms

Remote1y exp

“Built Syntriq, an AI-assisted deviation investigation platform for pharmaceutical manufacturers, owning the full stack from a 13-stage Python/FastAPI AI pipeline to a React report editor with source traceability. Stands out for combining strong technical execution with deep user discovery in a highly regulated FDA-sensitive domain, and for making pragmatic product decisions based on real QA investigator workflows.”

“Frontend engineer focused on technically demanding real-time visualization products, including dashboards for AI trainers and surveillance analytics tools. Stands out for combining React/TypeScript architecture, D3-based live visualizations, and production performance tuning to keep high-frequency data interfaces responsive under heavy load.”

Sriram Krishna

Screened

Mid-Level Software Engineer specializing in AI/ML and cloud-native platforms

Redmond, WA5y exp

“Backend/AI engineer who has built production LLM orchestration and agentic workflow systems in Python/FastAPI on Kubernetes across AWS/Azure. Demonstrated strong reliability engineering by debugging a real-world memory retention issue that caused latency spikes/timeouts, and strong data/performance chops with a PostgreSQL optimization that cut query latency from ~1.2s to ~15ms. Targets roles building scalable, guardrailed AI-driven workflow automation with robust observability and human-in-the-loop controls.”

“Software developer who actively integrates AI coding tools like ClaudeCode, Codex, and ChatGPT into day-to-day development for brainstorming, planning, and reducing boilerplate work. They show thoughtful awareness of agent limitations such as hallucinations and use markdown-based project context files to improve output quality.”

“Fullstack product engineer with strong AI application experience, including a provider-agnostic LLM routing layer spanning Bedrock, OpenAI, and Hugging Face. They pair hands-on technical depth with product instincts, having shipped customer-facing chat and workflow features that reduced support tickets by 38% and cut approval processing time in half.”

Ashutosh Talwalkar

Screened

Mid-level Software Engineer specializing in frontend and full-stack SaaS platforms

Santa Clara, CA7y exp

“Frontend-focused product engineer who owned the Quickwork automation platform’s architecture from 0 to 1, including a major migration from a monolithic frontend to microfrontends with Module Federation. Particularly strong in complex operational UX: real-time execution monitoring, analytics dashboards, API contract design, and performance-sensitive React/TypeScript systems for B2B SaaS workflows.”

Volodymyr Pisotskyi

Screened

Junior Full-Stack Engineer specializing in AI-powered web applications

San Francisco, CA2y exp

“Full-stack engineer building production AI/RAG systems for benefits workflows, including a state-level deployment that introduced filestore-based evaluation and improved answer correctness by about 30%. Strong across Next.js, backend infrastructure, and AI evaluation tooling, with hands-on experience in LangChain/LangGraph, Langfuse, accessibility-minded UI work, and zero-to-one product leadership in fast-moving environments.”

Hashim Kalam

Screened

Junior Software Engineer specializing in backend systems and applied AI

Colombo, Sri Lanka3y exp

“Full-stack and backend-oriented engineer with experience spanning customer-facing web products, LLM-based multi-agent systems, and enterprise Go microservices. They’ve worked on a ticketing/payments platform with Stripe, an NLP-to-2D-CAD MVP, and AI orchestration using LangChain, OpenAI, and Gemini, showing a mix of product thinking, backend architecture, and applied AI experimentation.”

“Software/product engineer who owns customer-facing internal platforms end-to-end, with deep experience building data pipeline health and data quality tooling (near-real-time alerting and ops dashboards). Strong in React/TypeScript + Python REST architectures and microservices with RabbitMQ, emphasizing reliability patterns (idempotency, DLQs, correlation IDs) and fast, safe iteration via feature flags, testing, and observability.”