Vetted OpenAI API Professionals

Kunal Mahato

Screened

Mid-level Software Engineer specializing in AI, full-stack systems, and platform engineering

Virginia, USA6y exp

“Full-stack/AI engineer with experience spanning supply-chain product deployments, biomedical agentic search, and research-grade RAG evaluation. Stands out for owning customer-facing migrations at scale (including 216,000 historical shipments), building measurable LLM systems, and pairing AI experimentation with rigorous evals, rollout controls, and auditability.”

“Built and iterated an end-to-end virtual waiting room for a real-time ticketing prototype, making concrete architecture tradeoffs (polling + Redis Pub/Sub) and improving performance post-launch with Redis caching (+30% throughput, -15% p99 latency). Also has hands-on experience building Spark/HDFS ETL pipelines with strong reliability/observability patterns and running disciplined NLP model evaluation loops on review-rating classification.”

“Built Taskline end-to-end as a solo founder: an AI-native operations platform for tradespeople with web and mobile apps, AI receptionists, invoicing, scheduling, and payments. Particularly interesting for teams seeking a zero-to-one full-stack builder who can turn LLM/agent capabilities into practical, low-friction products for non-technical users.”

“AI/full-stack product engineer with experience shipping agentic systems in both fintech and enterprise compliance contexts, including an Anthropic-powered compliance Q&A tool at American Express and a home-equity assessment experience for seniors. Stands out for combining strong product instincts, typed full-stack implementation, and rigorous LLM evaluation/monitoring practices to improve trust, adoption, and operational efficiency.”

“Runs two lean real estate companies remotely by building local on-the-ground contact networks and leveraging free-tier technology to keep total annual business costs under $100. Brings a cost-elimination and MVP/validation-first mindset, preferring to join an established company unless a clearly viable business idea emerges.”

“Backend/data engineer with hands-on production experience across GCP and AWS: built FastAPI microservices on Cloud Run and delivered AWS Lambda + ECS Fargate systems with Terraform/GitHub Actions. Strong in data engineering (Glue/Spark, S3/Redshift) and modernization (SAS to Python/SQL), with proven reliability and incident ownership—including cutting a 20+ minute reporting query to under 2 minutes.”

“Built a personal product, Pilly AI—an AI-powered e-commerce product Q&A widget embedded via a simple script tag and served via Cloudflare CDN—covering landing page, backend, database, and deployment end-to-end. Implemented OpenAI integration with prompt/context engineering, JWT-authenticated APIs, and Postgres (NeonDB), and successfully sold the product to a client while shipping in roughly two weeks.”

“AI/LLM engineer who built a production content-generation system for nursing education, combining multimodal RAG over proprietary PDFs (including images) with structured Cosmos DB data and external sources. Strong focus on production reliability—prompt-chaining with LangChain, validation/guardrails, and Azure-based monitoring/observability—plus experience designing Azure AI agents with tool integrations like Bing Search.”

“LLM/ML platform engineer with hands-on experience taking an LLM document summarization prototype into a production-grade service on AWS EKS, emphasizing low-latency inference, drift monitoring, and safe CI/CD rollouts (canary + rollback). Strong in real-time debugging of agentic/RAG systems (tracing, retrieval/index drift fixes) and in developer enablement through practical workshops (Docker/Kubernetes/FastAPI) plus pre-sales support via demos and benchmarks to close pilots.”

“Product-focused full-stack engineer (70/30 app vs infra) with Accenture experience and recent AI workflow work, shipping end-to-end systems from React/TypeScript UIs through FastAPI backends to Postgres. Built an AI-driven data extraction platform with async job APIs, strict schema validation, and strong observability, and has operated AWS ECS-based deployments with real incident mitigation (DB connection exhaustion/latency under traffic spikes).”

“Backend engineer who built an AI voice-driven calendar assistant using Python/Flask with a multi-agent architecture (CrewAI + OpenAI), including agent-specific memory management and summarization to handle token limits. Also has production performance optimization experience at Trendyol, adding Redis caching to speed up an advertisement retrieval endpoint and improve page load experience.”

Rushir Bhavsar

Screened

Intern AI/ML Engineer specializing in LLMs, MLOps, and distributed training

1y exp

“Founding AI engineer (June 2024) at Talon Labs who built and productionized an LLM-powered chatbot for interacting with proprietary supply-chain documents, deployed at large scale (25–100,000 users). Experienced with RAG/LLM orchestration (LangChain, LlamaIndex, Groq AI) and production ops tooling (Kubernetes, Docker, Kubeflow, Airflow), with a metrics-driven approach to evaluation, observability, and stakeholder alignment.”

Manasa Reddy Nagendla

Screened

Mid-level Full-Stack Java Engineer specializing in microservices, cloud, and event-driven systems

Cincinnati, OH6y exp

“Software engineer at Procter & Gamble focused on warehouse/operations systems, building near-real-time order/inventory visibility using Java/Spring Boot, React, Kafka, PostgreSQL, and Redis with measurable latency and load-time gains. Also shipped internal LLM/RAG knowledge assistants grounded in company runbooks and workflows, implementing guardrails and an evaluation loop that drove concrete retrieval improvements (document chunking) and regression prevention.”

Jake Lee

Screened

Junior Full-Stack/Systems Engineer specializing in AI, embedded systems, and healthcare apps

Boston, MA3y exp

“Led architecture for “Solstice/Solstis,” a safety-aware, hands-free AI medical assistant that guides users through minor emergencies with a structured, state-machine-driven LLM agent integrated with device hardware. Built RAG grounded in Red Cross procedures plus guardrails, fallbacks, and emergency escalation, and improved real-world usability by shifting from open-ended chat to a deterministic step-by-step workflow measured via completion rate, repeat prompts, and latency.”

“Built and deployed a GenAI-powered PhD career intelligence platform at NYU that maps academic backgrounds to career paths and converts long academic CVs into job-ready resumes. Stands out for treating LLM systems as structured production pipelines—combining NLP extraction, embeddings, orchestration, and AWS deployment—to improve recommendation quality and cut resume preparation time by 70%.”

“Built and deployed an AI-driven expense categorization workflow integrating OpenAI API and PGVector to automate general ledger coding. Stands out for combining LLM/embedding architecture with finance operations context, stakeholder-facing deployment ownership, and measurable impact of roughly 30%+ reduction in manual coding effort.”

“Built an internal RAG assistant for financial documents using FastAPI, OpenAI APIs, and vector search, improving document search speed and reducing manual effort for the business team. Stands out for a pragmatic approach to AI engineering: uses AI heavily for productivity, but keeps human judgment central and has designed retrieval, validation, and summarization workflows end-to-end.”

“Developer with a pragmatic, disciplined approach to AI-assisted coding: uses tools like Copilot, ChatGPT, and Gemini to speed up debugging, optimization, unit testing, and documentation while maintaining ownership of design and code quality. Interested in expanding from single-agent workflows into multi-agent setups for larger coding tasks and stays current through hands-on use and AI ecosystem updates.”

“AI/full-stack engineer in gaming analytics who joined Omnic.ai at a 2-person stage, helped grow with the company, and built both backend and frontend for real-time gameplay analysis products. He combines computer vision production experience with LLM/RAG systems work, and has already led 4 employees while shipping 12 models in a fast-moving startup environment.”

MohmmadHussain Syed

Screened

Mid-level Full-Stack Engineer specializing in customer-facing web platforms

USA4y exp

“Full-stack product builder who described owning an AI-powered journaling platform end to end using React/Vue, FastAPI, Supabase, PostgreSQL, and Hugging Face APIs. Also shipped a customer-facing document upload feature for First National Bank by solving micro frontend integration issues with web components, and has built internal tooling such as a GitHub PR review app.”

“Frontend-leaning full-stack engineer with strong ownership in network observability and analytics products, including BT Group's SMARTS platform and SSpain.ai at Texas A&M. Stands out for building data-dense, near-real-time dashboards and shaping products end-to-end across React/Angular frontends, FastAPI backends, PostgreSQL, AWS, and even React Native mobile surfaces.”

Saumay Killa

Screened

Mid-level Full-Stack Engineer specializing in AI SaaS and web applications

New York, NY3y exp

“Built a career platform feature end-to-end that generates tailored resumes and cover letters using a React/TypeScript frontend, Postgres, and AWS Lambda/SQS backend. Strong in event-driven, serverless architecture and pragmatic product iteration, with a quantified 60% improvement in onboarding completion after redesigning the UX with resume parsing and a multi-step flow.”

“Java/Spring Boot engineer with startup-style ownership experience across e-commerce, banking, and healthcare analytics. Stands out for driving a monolith-to-microservices migration with Kafka that improved checkout reliability under peak load, while also contributing full-stack with Angular and supporting production operations end to end.”

“Customer-facing technical professional with experience supporting LLM/agentic-style workflows and complex integrated systems (APIs, backend logic, databases). Partnered with sales/customer teams at Radix Health to onboard new clients in phased prototypes, translating non-technical requirements into technical scope and implementing core product changes to tailor the appointment-booking solution for providers.”