Vetted OpenAI API Professionals

SaiDheerajReddy Gadikota

Screened

Mid-level AI Engineer specializing in agentic systems and enterprise LLM platforms

USA, USA4y exp

“Current AI engineer at a startup who has spent the last year architecting multi-agent systems for software development workflows. Stands out for combining LLM speed with engineering discipline—using tools like Pydantic, LangGraph, and LangChain to build reliable, production-ready agent workflows with validation, routing, and retry logic.”

“LLM/RAG engineer at Connex AI who built and deployed a production healthcare agent to extract clinical insights from medical data/notes. Strong focus on real-world reliability—hallucination mitigation (citations, schema validation, confidence thresholds, rejection logic), custom LangChain orchestration (query rewriting, fallback paths), and production evaluation/observability—while collaborating closely with clinical SMEs to ensure clinical fit and time savings.”

Yousef Abdelsalam

Screened

Junior Software Engineer specializing in Odoo, web performance, and backend systems

Orlando, FL2y exp

“Full-stack developer who shipped LLM-powered customer support automation, including an AI call center designed for always-on, high-concurrency real-time phone handling. Also built a WhatsApp lead-conversion chatbot using Zapier webhooks, Redis state, and Twilio messaging, and reports measurable outcomes (+11% customer satisfaction, ~7% cost reduction) while using GPT-4.1.”

“Built and shipped production LLM-driven pipelines for clinical data processing, turning semi-structured inputs into validated structured outputs for downstream analytics. Emphasizes predictability and safety via strict JSON schemas, state-machine orchestration, backend-controlled tool calling, and robust fallbacks (rule-based checks/manual review) plus monitoring and offline/online evaluation loops; also has experience hardening workflows against messy ERP/finance data with idempotency and state tracking.”

“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

Screened

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.”

Jorge Reinoso

Screened

Senior Software Engineer & Tech Lead specializing in real-time simulation, VR, and networking

Santiago, Chile9y exp

“Unity/C# tech lead who shipped a VR co-op shooter (ChronoStrike) with a network-synchronized time-dilation mechanic, extending Photon Fusion prediction/reconciliation to handle variable timescales and reporting major stability/performance gains (90 FPS Quest 2; rubber-banding reduced from ~15% of sessions to zero). Also integrated GPT-3.5-powered NPC dialogue with scripted fallbacks for a Transport Canada training simulator, and built a cross-platform VR+mobile neurofeedback app integrating NeuroSky EEG via native iOS/Android plugins.”

Ahmad Rayyan

Screened

Entry-level Full-Stack Engineer specializing in Applied AI and multi-agent systems

Pakistan1y exp

“Built both traditional full-stack products and advanced LLM systems, from a React/Flask dashboard used by instructors to monitor GitHub contribution patterns to multi-agent benchmark infrastructure at Analytiverse. Particularly strong in evaluation-heavy AI engineering: designed executable verifiers, force-zero anti-reward-hacking checks, and token-optimization strategies that delivered a 40-point pass-rate lift and 90x token reduction on SwarnBench tasks.”

Gowtham Manikanta Chilukabathula

Screened

Entry-level AI and Data Analyst specializing in LLMs and analytics

Memphis, TN1y exp

“Candidate brings a blend of AI, analytics, and go-to-market support experience through an AI/data internship and graduate assistant role. They analyzed data across 50+ organizations to identify high-fit outreach segments, improving targeting efficiency by about 28%, and also built/reviewed GPT-4 and LangChain-based outbound messaging systems with strong quality controls.”

“Early-stage product engineer who built an AI persona chat system end to end at Super Intro, spanning Next.js frontend, GraphQL/real-time backend, retrieval memory, and LLM-based matching. They combine strong TypeScript rigor with practical AI systems design, and cite measurable impact including ~40% engagement growth, ~30% recall improvement, and lower LLM costs in production.”

“Engineer with growth-stage startup experience on a 6-7 person cross-functional team, working across backend, data, and frontend systems. They’ve driven concrete improvements to high-volume data ingestion pipelines through batch processing and database optimization, and have built B2B SaaS data platforms for enterprise customers with multi-tenant support, integrations, and scalable backend services in Python and Go.”