Founding Harness Engineer – AI Agents

• Build the agent runtime: context, tool choice, approval waits, and knowing when to act, ask, or stay quiet
• Write and keep tuning the system prompts; ensure proactive behavior without spamming the team channel
• Own the eval and regression harness; test prompt changes like code
• Make long-running work survive interruptions, retries, and flaky APIs
• Implement guardrails, including approval gates for risky actions and strict customer data separation
• Work directly with the founder and early users, turning feedback into shipped behavior

• You've shipped tool-using LLM agents to real users in production. Demos and prompt wrappers don't count
• Good instincts for agent initiative, and the test results to back them up
• Hands-on experience building eval and regression suites for LLM behavior
• You understand safe tool execution, prompt injection, and multi-tenant data risk
• Solid backend skills in Python or TypeScript (async jobs, retries, state)
• You take a fuzzy problem from prototype to production and can explain the tradeoffs along the way
• Excellent written and verbal communication; you can explain a tradeoff to a founder or a user without a whiteboard
• Nice to have: MCP, or integrations with tools like Slack, Gmail, Notion, or Linear
• Nice to have: Eval and tracing tools such as Braintrust, Langfuse, or LangSmith
• Nice to have: You've been an early engineer at a startup before and still liked it

• Founding equity
• A direct line to the founder and early users, with no layers in between
• Remote from Latin America or Eastern Europe, with solid overlap with US Pacific time
• The tools and models you need to do the job properly
• A small, experienced team that trusts you to run your own work