AI Engineers, fractional.
Builders who ship agent loops, retrieval pipelines, eval harnesses, and LLM-backed product features — and leave behind repos, not decks.
When to bring one in
- Shipping an agentic feature your team has been circling for a quarter
- Standing up evals, tracing, and structured outputs before scale breaks you
- Hardening a vibe-coded prototype into production infrastructure
- Engagements
- 2–10 days scoped build · Fractional 1–3 days/week · Embedded sprint with your team
- Vetting
- Public proof of shipped AI work — repos, production systems, measured outcomes. Reviewed by humans.
- Start
- Shortlist in days, not months. Start scoped, expand on results.
- Network
- 6 ai engineers listed with public profiles.
In the network
Profiles link to public proof — showcases, repos, and source notes. Matching always runs through a brief so we can pair the right person with your exact problem shape.
@dexter-horthy
HumanLayer founder — team-scale Claude Code and context engineering
view profile → A Anand Chowdhary@anand-chowdhary
Continuous Claude builder — long-running Claude Code PR loops
view profile → U unohee@unohee
OpenSwarm maintainer — multi-agent Claude Code orchestration
view profile → N nadeem1@nadeem1
Athena Flow builder — structured workflows for AI coding agents
view profile → M mordymoop@mordymoop
PlateSpinner maintainer — Kanban orchestration for AI coding agents
view profile → E Edward Lawless@edward-lawless
AI systems builder — game-AI, healthcare data infra, research automation
5 public showcases →Need an AI Engineer?
Send a short brief describing the outcome you need. We'll reply with a proof-backed shortlist — or tell you honestly if we don't have the right match.
Other roles
AI Product Leaders
Product managers and founders who run AI-native product orgs.
2 in network view → ~/hire/ai-engineering-leadershipEngineering Leaders
Leaders who have rewired real engineering orgs around AI.
5 in network view → ~/hire/ai-ops-automationAutomation & Ops
Workflow automation across n8n, agents, and internal tooling.
4 in network view → ~/hire/ai-dataData & ML
Structured outputs, data pipelines, and eval-driven LLM systems.
3 in network view → ~/hire/ai-marketingMarketing & Content
Growth and content operators with AI-native production systems.
2 in network view →