Vetted Retrieval-Augmented Generation (RAG) Professionals

“AI engineer and current tech lead building a RAG-based multi-agent QA platform for financial document analysis at significant scale (40,000-50,000 documents). They combine Python, CrewAI, FastAPI, Hugging Face embeddings, Pinecone, and AWS SageMaker to deliver retrieval, calculation, summarization, forecasting, and visualization workflows, while leading a small cross-functional team.”

“Hands-on engineering leader who has scaled teams quickly (hired 20 engineers in 4 months) and led major architecture shifts including monolith-to-microservices and serverless, async AI-driven medical data ingestion/search. Also drove a versioned-inventory redesign with auditability and rollback that reduced operational errors by 22%, and demonstrates strong incident response with clear stakeholder communication.”

“AI/full-stack engineer with hands-on experience shipping LLM-powered operational workflows in claims and Medicaid contexts. They built end-to-end TypeScript/React/Node systems with RAG, structured outputs, evals, and human-in-the-loop controls, and can point to concrete impact including 45% lower triage time, 38% better retrieval accuracy, and major manual-effort reductions.”

“AI product leader working at TAU Ventures Innovation Lab and previously at Verint and NYSHEX, with a track record of turning legacy and ambiguous AI opportunities into shippable, human-centered products. Notably led Verint’s evolution into a low-code AI orchestration platform with 20+ capabilities and measurable gains in CSAT, handle time, and recurring revenue, while consistently emphasizing trust, workflow fit, and human-in-the-loop design.”

“Product leader working at the intersection of AI, data governance, and industrial/energy operations. They have led a major finance-platform rewire for solar and wind asset forecasting at NextEra and previously built an AI-assisted field service app for fire alarm technicians across four business units, showing unusual depth in both enterprise data architecture and safety-critical mobile workflows.”

Yuchen Shen

Screened

Junior Full-Stack Engineer specializing in AI and graph-based applications

Sunnyvale, CA2y exp

“Front-end engineer with experience at Walmart and Sam's Club building sophisticated browser-based UIs, including an internal AI chat experience that combined chat, document rendering, editing, and visualization in one workflow. Stands out for pairing modular React/TypeScript architecture with hands-on browser performance debugging and Apollo/GraphQL optimization for highly interactive enterprise interfaces.”

“Full-stack product builder with strong GTM and applied AI experience, including end-to-end ownership of a production lead intelligence platform that combined React/TypeScript, Python services, external data enrichment, and LLM orchestration. Notably reduced SDR research time from 15-20 minutes to under 2 minutes per account and also drove an 8% revenue increase at Finding Pi by building a customer segmentation framework from analysis of 45k+ users.”

“Frontend-focused engineer with experience spanning healthcare, enterprise analytics, and real-time trading products. They have owned React/TypeScript dashboard surfaces end-to-end, including a hospital patient dashboard that cut latency by 50%, and have also shaped backend WebSocket contracts to make real-time systems scale.”

Ilya Kravchenko

Screened

Executive engineering leader specializing in AI-enabled SaaS and internet-scale platforms

Thousand Oaks, CA20y exp

“Engineering leader with a rare blend of SaaS, robotics, and AI systems experience, most recently leading a 21-engineer org under the CTO. They pair strong people/process leadership with hands-on architecture depth, driving dramatic delivery improvements while also building grounded LLM support tooling for warehouse operations where accuracy directly impacts physical execution and customer outcomes.”

“Former psychiatrist and educator turned product leader with a strong human-centered AI philosophy. Has led AI-native SaaS and mobile products, managed large cross-functional orgs, and brings distinctive edtech experience including reducing tutor rematch rates by 52% while protecting the tutor-student relationship.”

Keerthana Kondabathini

Screened

Senior Full-Stack Engineer specializing in healthcare and financial platforms

5y exp

“Software engineer with experience spanning healthcare platforms at UnitedHealth Group/Optum and B2B SaaS systems at Zoho. Has worked on a startup-like internal product for intelligent medical document processing using microservices on Azure, while also building React dashboards, backend APIs, and Python automation to support clinical and business operations.”

“Full-stack engineer with hands-on ownership of an internal LLM platform, spanning React/NestJS development, PostgreSQL schema design, multi-provider model integrations, and chat/eval pipelines. They also show strong production engineering instincts, having resolved Cognito throttling failures via tracing and led an observability migration to Signoz that materially improved incident diagnosis speed.”

“Enterprise AI and digital transformation leader who has delivered 120+ automation and AI solutions across healthcare, finance, supply chain, and shared services, with outcomes including €52M annual savings at Philips and major operational gains at Alto Pharmacy. Combines product ownership, hands-on LLM/RAG prototyping, and strong governance instincts for regulated environments, making them especially compelling for enterprise AI deployment roles.”

Aaron Mcanerney

Screened

Mid-level Backend Software Engineer specializing in data platforms and reporting

Pleasanton, CA5y exp

“Built a production Medicare Q&A chatbot using OCR (pytesseract), LangChain chunking, ChromaDB embeddings/retrieval, and an Ollama LLM. Thinks in terms of practical tradeoffs (cost, model selection, static vs frequently-updated corpora) and emphasizes deterministic testing plus observability for reliable LLM workflows; also has experience automating non-technical teams' pain points (e.g., recruiting event integration).”

Prashant Singh

Screened

Mid-level Backend/Platform Engineer specializing in data pipelines, reliability, and AI-assisted ingestion

8y exp

“Backend engineer who built and scaled a blockchain-based e-voting platform at early-stage startup Elemential Labs, balancing decentralization with real-world operability by centralizing control-plane components while keeping the ledger immutable. Has hands-on experience migrating high-throughput ingestion from Kafka to AWS Kinesis with parallel cutover, strengthening data integrity and read-after-write consistency (Elasticsearch), and hardening pipelines against silent data-quality failures via anomaly detection and self-healing automation.”

“Senior product leader with a track record of rebuilding complex enterprise products in legal tech, martech, and financial data. Notably transformed Recommind's eDiscovery UX ahead of its $163MM acquisition and now builds high-scale LLM-powered SEC filing analysis at FeeLogic, combining strong AI product judgment with a human-centered philosophy for high-stakes workflows.”

“CTO/AI executive with repeated 0-to-1 leadership and founder experience across banking software, cloud, and fintech. Most recently, as a fractional CAIO, built a 50+ person team and launched 3 products in 9 months generating $10M+ new revenue; previously founded Trilogy (200+ clients in 7 countries) and created cloud tech that helped drive a $35M acquisition by VMware.”

“Built and owned end-to-end production Conversational AI and RAG systems at Nike for customer support and product search, with strong evidence of measurable impact. Combines LLM product thinking with solid platform engineering, including evaluation pipelines, monitoring, safety controls, and reusable FastAPI frameworks that improved both user outcomes and team velocity.”