Vetted Multi-Agent Systems Professionals

“Chief AI Strategy at startup Zenera with 30 years in technology strategy/design, experienced in building business plans across startups and large enterprises (projects, new products, and M&A). Deeply familiar with enterprise AI go-to-market challenges (slow procurement/pilot cycles) and preparing for VC expectations (e.g., targeting a16z) by emphasizing unique tech and paying customers.”

Jesse Olson

Screened

Executive AI technology leader specializing in agentic AI and enterprise transformation

22y exp

“Candidate is exploring a startup in the autonomous agentic AI space and is approaching it with a disciplined founder mindset. They are evaluating market opportunity, competition, customer pain, ROI, technical feasibility, and MVP options while already speaking with potential customers across verticals to validate needs and buying processes.”

Farabi Hassan

Screened

Principal Product Leader specializing in AI-powered enterprise and marketplace platforms

Seattle, WA13y exp

“Product leader with experience at Zillow, Amazon, and Chewy, focused on high-scale ML and UX-driven product improvements. Has led end-to-end rebuilds and launches that delivered measurable business impact, including a 23% conversion lift in lead routing, 40%+ reduction in delivery-related customer contacts, and 10%+ ecommerce conversion gains.”

Daozheng Chen

Screened

Staff Full-Stack AI Engineer specializing in FinTech and Enterprise SaaS

San Jose, CA12y exp

“Full-stack engineer with Yahoo Finance experience building AI-powered investment and analytics features. They combine modern TypeScript/React/NestJS development with strong backend systems skills in PostgreSQL, Redis, Kafka, and Kubernetes, and have driven architectural improvements from synchronous workflows to event-driven microservices in a high-traffic financial environment.”

“Product leader focused on human-centered AI, with standout experience leading agentic AI strategy for Microsoft’s Cloud Supply Chain during a major GPU demand surge after the OpenAI partnership. They combined platform thinking, embedded AI UX, and influence-based leadership to drive adoption, cut manual effort by 40%, reach 2,000 MAU, and help protect $50M in at-risk revenue, while also building an AI quiz coaching tool for middle-school academic Olympiad students.”

“ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.”

“ML/NLP engineer with experience at NVIDIA and Cruise building production-grade AI systems across genomics/biomedical research and autonomous vehicle data. Has delivered multimodal LLM pipelines, large-scale entity resolution, and hybrid semantic search (BERT embeddings + FAISS + Elasticsearch), with measurable impact (≈40% accuracy/retrieval gains; ≈30% data consistency improvement) and strong MLOps practices (Kubernetes, CI/CD, MLflow, Prometheus/Grafana).”

David Lapsley

Screened

Executive Engineering Leader specializing in AI infrastructure and cloud platforms

Tampa, FL14y exp

“Founder building Shipkode.ai, an enterprise SaaS product using generative AI to automate the front half of the software development lifecycle—from idea and customer feedback to engineering-ready specifications—with a beta planned for the first week of April. Has spoken with 24+ VCs over two years and mentors cybersecurity startups through the Tampa Bay Wave accelerator, emphasizing rigorous customer discovery to avoid misaligned product development.”

Britney Russ

Screened ReferencesStrong rec.

Executive product leader specializing in consumer technology and EdTech

Los Angeles, CA13y exp

“Senior product leader from Codecademy who has spent roughly a decade building and mentoring cross-functional organizations while leading major strategic pivots in education. Most notably, they repositioned Codecademy toward a new learner segment and launched an AI-native learning platform that tripled signup rates, while also creating new revenue streams like live learning and accessible AI workshops.”

Abhinav Bandaru

Screened

Junior Data Scientist specializing in Generative AI and agentic LLM systems

San Jose, CA1y exp

“LLM/agentic-systems builder who has shipped production tools for investment research and procurement insights, including a company screener that processes thousands of conference-listed companies using FireCrawl + Google Search + Gemini. Demonstrates strong orchestration expertise (LangGraph multi-agent graphs), performance optimization (async/batching to sub-30s), and pragmatic reliability/evaluation practices with stakeholder-friendly UX (real-time cost tracking and model/parameter toggles).”

“CMU engineer with hands-on experience building full-stack AI products across internships and academic projects, including a Microsoft real-time multimodal assistant and a Cursor-like coding agent. Stands out for combining low-latency systems engineering with strong product instincts, shipping AI tools that improved latency by 35%, cut grading time from five days to under 10 minutes, and reduced user resubmissions by 45%.”