Vetted Distributed Systems Professionals

Stephen Koo

Screened

Senior Software Engineer specializing in LLM infrastructure and AI inference platforms

New York, NY8y exp

“Google Workspace AI engineer who owned major AI assistant infrastructure end-to-end: React/TypeScript UI, a Node.js context-aggregation gateway on Cloud Run, and a Go inference layer on GKE serving Gemini. Built and productionized Gmail RAG + agentic workflows with rigorous evals and guardrails, and has a strong track record of measurable impact (latency, engagement, acceptance-rate lifts) and zero-incident migrations using feature flags/strangler patterns across multiple ML teams.”

“Highly experienced robotics software engineer building ROS/ROS2 systems for fleets of autonomous mobile robots (Clearpath Jackal/Husky and custom platforms), spanning localization, navigation, and multi-robot coordination. Has published work at ICRA (including RL-based local planning and heterogeneous robot coordination via a ROS-to-ZMQ bridge) and maintains open-source ROS modules, with strong simulation, debugging, and CI/CD practices.”

“Backend/data engineer with deep healthcare data experience (FHIR, de-identification) across both GCP and AWS. Has built and operated production microservices and ETL pipelines (FastAPI, Dataflow, Glue) with strong reliability practices, and led modernization of a legacy SAS compliance reporting system to cloud services with validated parity and stakeholder-facing Looker comparisons.”

Kaiqi Zhang

Screened

Senior Full-Stack Engineer specializing in cloud-native SaaS and AI applications

Bellevue, WA13y exp

“ML/LLM engineer with hands-on experience shipping production RAG systems at Google Clinical Search and GenAI recommendation/summarization features in Meta Ads. Stands out for combining research-to-production execution with rigorous grounding, evaluation, safety checks, and reusable Python platform components that improved both reliability and team velocity.”

“Hands-on engineering leader currently at Vianai (GenAI enterprise applications) building AI-assisted data exploration/insights products with Python and React. Previously Corporate VP of Digital Health at Samsung Electronics, where they helped close key partner deals by demonstrating API-driven openness and led a major Samsung Health modernization from monolith to microservices for horizontal scalability and faster, safer iteration.”

“Game engineer with hands-on experience shipping systems for Horizon Worlds, including a notification platform that unlocked friending, invites, and achievement/prize UX. Also brings applied LLM gameplay experimentation, multiplayer networking/debugging expertise, and cross-platform VR/mobile experience spanning Meta Quest and Android.”

Jacob Zimmerman

Screened

Director-level Engineering Platform leader specializing in cloud infrastructure, SRE, and SaaS compute

New York, NY19y exp

“Longtime early-stage startup operator (since 1998) now running a solo consulting practice focused on SaaS infrastructure and platform strategy. Former angel investor in a medical information SaaS company that went public, with a strong focus on making prototype/demo systems enterprise-ready through efficiency, reliability, and performance improvements, and a nuanced view of how AI/LLMs may change engineering team models.”

Christopher McLean

Screened

Executive engineering leader specializing in security, privacy, and high-scale infrastructure

Brookline, MA18y exp

“Veteran operator from top-tier tech companies including PayPal, LinkedIn, Stripe, Facebook, and Merge, now seeking the right startup idea to found. Brings hands-on angel investing experience across 5 startups in the EU and US plus additional exposure through X-Stripe Angels, giving them both operator and investor perspective.”

“Engineering leader/player-coach who built and validated a preference-based recommendation engine using clustering, including generating test data to evaluate how clusters evolve over time. Has SRE/DevOps experience and has owned production incidents end-to-end (logging-driven RCA and refactoring patterns that failed at large data scale). Emphasizes quality and platform stability via unit, integration, and load testing, and has managed performance via regular 1:1s and PIPs.”