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Vetted OpenAI Professionals
Pre-screened and vetted.
Senior AI & Full-Stack Software Engineer specializing in LLM platforms and MLOps
Senior Full-Stack Engineer specializing in cloud-native web platforms and LLM-powered features
Senior AI/ML Engineer specializing in Generative AI, RAG, and multimodal LLM systems
Senior Full-Stack Engineer specializing in React/Next.js and cloud-native systems
Director-level Lead Full-Stack Engineer specializing in scalable SaaS and AI automation
Mid-level Robotics & AI Researcher specializing in learning-augmented task and motion planning
Senior Software Engineer specializing in Python backend, microservices, and cloud/DevOps
Senior Full-Stack Software Engineer specializing in Python/Django, React, and AWS
Mid-Level Software Engineer specializing in backend, SaaS, and AI integrations
Mid-level Generative AI Engineer specializing in RAG systems and AI-powered education tools
Mid-Level ML/AI Engineer specializing in LLMs, RAG, and multi-agent systems
Senior Full-Stack Python Engineer specializing in AI/LLM-powered web applications
Senior Full-Stack Software Engineer specializing in AI/LLM-powered web applications
Adib Firoz
Mid-level Frontend Developer specializing in React and Next.js
“Frontend engineer who has built and owned products end-to-end, including a healthcare app with live video monitoring and a stock market dashboard. Emphasizes scalable UI architecture via reusable components and shared schemas, plus performance/SEO improvements using Lighthouse and modern loading/minification techniques. Has experience shipping time-sensitive features like payment integrations with continuous QA support.”
Jatin Soni
Mid-level Software Engineer specializing in Generative AI and scalable backend systems
“Backend/AI engineer with production experience in legal tech: built a high-scale licensing/subscription API (FastAPI/Postgres/Stripe) and shipped a RAG-based chatbot for an eDiscovery platform. Designed a robust legal document ingestion workflow that processes thousands of documents into a searchable vector index with clear retry/escalation logic, and has demonstrated measurable Postgres performance wins (200ms to 10ms) using EXPLAIN ANALYZE and composite indexing.”