Vetted AI Agents Professionals

“Asset Management Risk professional at Fidelity Investments who built and productionized an agentic RAG platform enabling compliance and analysts to query 10,000+ fund documents with cited answers in seconds. Implemented structure-aware semantic chunking (AWS Textract), hierarchical retrieval, and hybrid search to raise accuracy from 68% to 94%, and built an evaluation framework tracking accuracy/latency/cost/hallucinations—delivering 40+ hours/month saved and zero critical production failures.”

“Amazon Fire TV Devices engineer who built and shipped a production LLM-powered lab triage and validation system that grounds recommendations in internal runbooks/known-issue data and pushes evidence-based actions via dashboards and Slack. Emphasizes safety and measurability with structured JSON outputs, replay-based evaluation on historical incidents, and production metrics (e.g., disagreement rate and time-to-first-action), plus cost/latency optimizations like caching, batching, and rule-based fast paths.”

“Built and shipped a production-grade GenAI Fraud & Compliance Investigation Copilot for a large US bank, integrating OCR docs, structured data, and prior case history to generate grounded, regulator-friendly summaries and red-flag highlights. Demonstrates strong end-to-end LLM systems engineering (LangGraph/LangChain, hybrid retrieval with FAISS+BM25, guardrails/citations, streaming/latency optimization) plus rigorous evaluation and close partnership with compliance stakeholders.”

Shreya B

Screened

Mid-level Software Engineer specializing in backend, cloud-native, and GenAI systems

Redmond, WA5y exp

“Software engineer with strong Java/Spring Boot backend depth and hands-on full-stack experience building AI-powered enterprise knowledge assistants and customer-facing order tracking systems. Stands out for combining RAG/LLM product work, event-driven microservices, and user-trust-focused product iteration, including shipping prototypes that became the basis for broader production workflows.”

“Full-stack engineer who built and owned a production real-estate search platform (advanced search + saved-search alerts) using Next.js App Router/TypeScript with a NestJS + Postgres + Elasticsearch/Kafka backend. Demonstrated strong performance engineering (map search FPS ~20→60, ~80% latency reduction) and backend scalability (optimized alert-matching queries and orchestrated notification workflows with Airflow/Redis), with measurable post-launch engagement gains (+27% returning users).”

Melbourne Brown

Screened

Senior Software Engineer specializing in AI-driven cloud-native platforms

Atlanta, GA12y exp

“Engineer with unusual breadth: from a tiny startup building racehorse medical-record systems on credit-card chips for live racetrack demos to modern AI-powered contract intelligence platforms in production. Brings hands-on full-stack and backend depth across React, Python, .NET, PostgreSQL, Kubernetes, and Azure, with a track record of making complex, reliability-sensitive systems work in real-world conditions.”

Syed Husain

Screened

Senior Software Engineer specializing in AI and healthcare platforms

San Francisco, CA5y exp

“Backend/ML engineer who has moved from enterprise energy systems at Chevron into healthcare AI, including co-founding a medical billing AI startup and building real-time clinical assistant infrastructure at Humana. Particularly strong in production LLM systems, streaming backend architecture, and regulated healthcare workflows where latency, reliability, auditability, and user trust all matter.”

“Healthcare data platform builder with experience at Aetion delivering a rule-based EMR/EHR ingestion and validation framework that cut onboarding from 8–10 weeks to hours and unlocked $30M+ in revenue over ~3 years. Motivated to found an AI/agent-driven healthcare solution, with a specific interest in using PET scans, doctor notes, and treatment data with LLMs to help predict cancer progression and guide next-step treatments.”