AI Automation Engineer

Role overview A hands-on automation engineering role focused on finding high-leverage workflow problems and shipping reliable AI-assisted systems that improve revenue per employee. The work spans process discovery, build, rollout, monitoring, documentation, and measured adoption, with a clear bar that demos do not count and systems must work for the people who depend on them. The role operates within an AI-native team that uses AI to improve speed, quality, and judgment while keeping human review and controls in place.

Responsibilities - Map current workflows together with the people who actually perform the work - Rank automation opportunities by frequency, time, error cost, business value, and implementation risk - Build production automations across approved AI models, APIs, data sources, and workflow tools - Add validation, retries, logging, alerts, access controls, and human approval where appropriate - Train users, document each system, measure adoption, and close gaps after launch - Track results through approved KPIs such as time saved, cost avoided, cycle-time change, quality, or revenue effect - Maintain existing automations and retire systems that no longer create value

Requirements - Two or three production automations with clear personal ownership - At least one measured result tied to time, cost, quality, revenue, adoption, or cycle time - Experience diagnosing a workflow before choosing a tool, rather than jumping to automation - Evidence of error handling, monitoring, data controls, and human escalation in shipped systems - An example AI automation workflow with an honest account of what failed or changed along the way

Benefits and work setup - Fully remote, full-time contractor role - Pay: $25 per hour - Candidates should state location, working-hour overlap, and start date in the application