AI Engineer

About the role

We are hiring an AI Engineer to build the AI and agent systems that run MDS. This is a pure individual contributor role focused on one thing: using Claude and modern agent tooling to replace manual work that currently depends on operator judgment. You are joining an established tech team. Our Tech Lead owns our app and the broader automation architecture. Our Automations Specialist keeps the existing Make, Zapier, and GHL workflows running. Your role is to sit alongside them as the AI specialist: identifying where a Claude-powered agent beats a traditional automation, designing and shipping those builds, and upgrading existing workflows with AI when it raises the ceiling. A representative project: take our event registration review workflow (Luma inbound, Airtable lookups, LinkedIn and web verification, outcome emails, currently about 20 minutes of manual work per registrant) and ship a Claude-powered agent that handles the enrichment and qualification end to end, with a reviewer surface for one-click human approval, a custom MCP connector to Luma, full audit logging in Airtable, a test harness, and a runbook. You own it from whiteboard to production to month-six maintenance. Key Responsibilities Agent and System Engineering Design and ship AI agent systems end to end using Anthropic's Claude (API, Agent SDK, Managed Agents platform) to automate complex multi-step workflows that currently depend on manual operator judgment. Build MCP (Model Context Protocol) connectors, including custom connectors for platforms that do not have them. Luma is our first target; you should be comfortable building similar integrations against arbitrary APIs. Use Claude Code as a core part of your daily engineering workflow to build, test, and maintain production systems, not just as a chat companion. Develop prompts and rubrics as engineered artifacts with eval sets, version control, and a feedback loop when the agent gets decisions wrong. You treat prompt quality as a testable property of the system. Build reviewer surfaces (email or Slack handlers, Airtable Interfaces, or lightweight Next.js apps on Vercel) appropriate to the use case. You pick the lightest surface that solves the problem and upgrade only when justified. Upgrading Existing Automations with AI Audit current Make, Zapier, GHL, and Airtable automations for opportunities where an AI layer would make them meaningfully better (smarter routing, better classification, personalization at scale, handling edge cases that currently break workflows). Propose, design, and implement AI upgrades to existing workflows in partnership with the Tech Lead and Automations Specialist. You do not rebuild for the sake of rebuilding. You upgrade where AI raises the ceiling. Hand off maintenance cleanly. Once a system is stable and documented, our Automations Specialist takes routine monitoring and fixes so you stay focused on the next build. Software Engineering Discipline Write production-grade code in Python and TypeScript / JavaScript, with idiomatic use of modern frameworks. Node.js and Next.js experience expected for web surface work. Operate a real engineering environment: Git-based version control, pull requests, code review with the Tech Lead, separate dev / staging / production environments, environment variables and secrets management, and reproducible builds. Build testable systems: unit tests where they matter, integration tests for external APIs, and eval harnesses for agent behavior. Every shipped system has a way to verify it still works. Set up observability: logging, error tracking, and monitoring so failures surface visibly rather than silently. Design idempotent webhook and event-driven pipelines with retry logic, dead-letter handling, and no half-applied state on partial failures. Proposing and Prioritizing AI Work Continuously audit MDS workflows for opportunities where an agent would replace meaningful manual effort. Quantify the opportunity and write up concrete build proposals with effort estimates and expected impact. Present proposals to the Tech Lead, who prioritizes against the broader technical roadmap. Stay current on new Claude models, Agent SDK features, MCP ecosystem developments, and emerging agent patterns. Bring what is worth adopting back to the team. Working with the Team Partner with the Tech Lead on architecture decisions that touch the app, shared infrastructure, or the broader automation layer. You own AI specifically; they own the overall technical picture. Coach the Automations Specialist on AI patterns as a peer, not a manager. Help them level up on prompt engineering, agent basics, and how to debug agent-backed workflows. No formal management responsibilities. Partner with Operations, Revenue, Community, and Events to understand the workflows behind the automations. You need to deeply understand what the humans currently do before you can replace it with an agent. Documentation Every system you ship has a README, an architecture note, and

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at Million Dollar Sellers? Share your experience