AI Workflow Engineer

Basata builds AI agents for healthcare practices that answer patient calls and process inbound clinical documents. The AI Workflow Engineer leads customer implementations from handoff through go-live, designing workflows and configuring AI agents while coordinating stakeholders, testing, and training.

Responsibilities:

• Own customer implementation projects (simultaneously) end to end, from contract handoff through go-live and the stabilization period that follows
• Manage internal & external stakeholders through a project’s lifecycle
• Regularly report status updates and provide clear communication to internal and external teams
• Run each project against defined phase gates, and hold the gate — a phase does not close because the date arrived
• Provide feedback to current program & project management office to continuously refine best practices and standardization
• Walk the current-state process on site — at the desk, with the people doing the work, not from a description of it
• Map workflows as swimlane process maps and validate them with the staff who will live with the result
• Diagnose why a process fails before designing the replacement, using data rather than the first plausible explanation
• Translate what you find into agent configuration, routing rules, extraction fields and escalation paths
• Own defect triage during testing, and decide what ships, what waits, and what was never in scope
• Run kickoff, discovery, UAT and training sessions with audiences that range from front-desk staff to physician owners
• Set expectations honestly, including when something will not work the way it was hoped
• Deliver the post-go-live review with the data to back it up

Requirements:

• 5+ years in program management, implementation, process improvement, business analysis or a comparable delivery role
• Bachelor's degree in business administration, engineering, or a related field — or equivalent practical experience
• A track record of running concurrent projects with real deadlines and real stakeholders, not just contributing to them
• Demonstrated structured problem solving: you can show how you found a root cause rather than how you fixed a symptom
• Direct customer-facing experience, meeting the customers/patients needs
• Comfort with ambiguity — early deployments do not come with a runbook, they produce one
• Lean/Six Sigma certification (Green Belt or Black Belt)
• Background in health tech, digital health, or practice management software
• EMR platform familiarity (NextGen, ModMed, AthenaOne, Veradigm. eClinicalWorks or similar)