About this role
We’re hiring an AI Engineer to build and deploy production-grade AI agent systems that replace manual, judgment-heavy workflows.
This is a pure IC role focused on one thing: using Claude and modern agent tooling to automate complex operational processes end-to-end.
You’ll join an established technical team:
A Tech Lead who owns the core app and architecture An Automations Specialist who maintains existing workflows (Make, Zapier, GHL, Airtable) You, as the AI specialist, identifying where agent systems outperform traditional automations—and shipping those solutions into production This is not a prototyping role. You’ll build real systems that run the business.
What You’ll DoDay to day, you will:
Design and ship AI agent workflows end-to-end using Claude API, Agent SDK, and MCP connectors Build custom connectors for platforms without native integrations Audit and upgrade existing workflows (Make, Zapier, GHL, Airtable) by layering AI where it meaningfully improves outcomes (routing, classification, edge cases) Write production-grade Python and TypeScript (Git workflows, tests, evals, observability, staging) Treat prompts as engineered systems (eval sets, versioning, feedback loops) Build lightweight internal tools (Slack handlers, Airtable Interfaces, or Next.js apps on Vercel) Identify and propose new AI opportunities, with clear effort estimates and ROI Stay current with Claude models, Agent SDK updates, and MCP ecosystem developments Coach the Automations Specialist on agent patterns and prompt engineering (no formal management) Document thoroughly: READMEs, architecture notes, and runbooks for maintainability
Example ProjectYou might:
Replace a manual event registration review workflow (~20 mins per registrant) with a Claude-powered agent that: Enriches and verifies applicants (LinkedIn + web data) Qualifies and routes decisions automatically Generates outcome emails Provides a one-click human review interface Logs everything in Airtable Includes test harnesses, monitoring, and runbooks You own projects end-to-end: from design → production → long-term maintenance.
Requirements
Have shipped real AI agent systems in production (not just demos or experiments) Work hands-on with Claude (Anthropic) and modern agent tooling Think in evals, not vibes — you measure and iterate systematically Are strong in Python and/or TypeScript Understand automation ecosystems (Make, Zapier, APIs, webhooks, data pipelines) Can balance speed and engineering rigor Communicate clearly with both technical and non-technical stakeholders
Nice to Have Experience with MCP (Model Context Protocol) Background in workflow automation or RevOps systems Familiarity with Airtable, Slack APIs, Next.js, Vercel Experience building internal tools or reviewer interfaces