Lead AI Process Engineer

Help us redesign how the world’s largest airline works. United is building the best airline in aviation history, and AI is central to how we run operations, serve customers, and support employees. On our AI Enablement team, you’ll rethink how work gets done across Airport Operations, Contact Centers, Network Planning, Revenue Management, Digital Products, and HR. This work is hard in the best way. It’s safety-critical, runs around the clock, and spans many systems, teams, and stakeholder groups. If you want your redesigns tested against real operating conditions, this is the place. You’ll own the business side of transformation. That means partnering with business leaders to redesign core processes end to end, then scaling them as AI-enabled operations that change how work actually gets done. You’ll work alongside Forward Deployed AI Engineers and technology teams, who own architecture and deployment, while you own process design, requirements, and business outcomes. Success is measured by changed operations and realized value, not just slide decks or pilots.

What you bring (minimum qualifications)

• Proven experience leading end-to-end business process engineering, or operational transformation in complex organization
• Demonstrated experience applying structured process improvement methods, such as Lean, Six Sigma, industrial engineering, process mining, value-stream mapping, or root-cause analysis.
• Working fluency in generative and agentic AI (models, agents, retrieval, evaluation, reliability, security, governance), enough to partner credibly with engineers
• A track record of redesigning complex processes across functions and systems and measuring the results
• Strong analytical thinking, executive communication, and facilitation skills
• Comfort with ambiguity and large-scale organizational change
• Ability to travel 30-40%, primarily domestic
• 3+ years of relevant work experience
• Must be legally authorized to work in the United States for any employer without sponsorship
• Successful completion of interview required to meet job qualification
• Reliable, punctual attendance is an essential function of the position

What sets you apart (preferred qualifications)

• Enterprise generative or agentic AI implementation experience
• Process mining (Celonis, Signavio), automation platforms (Power Platform, UiPath), or Microsoft AI ecosystem familiarity
• Familiarity with enterprise AI ecosystems such as Microsoft Azure AI, Azure OpenAI, Microsoft Copilot or equivalent AI platforms.
• Lean Six Sigma Black Belt or equivalent
• Responsible AI governance or risk management experience
• Airline, transportation, or other complex operations background
• Experience leading transformations where AI changed roles, decisions, and controls
• 5+ years of relevant work experience

Description:

Find the right opportunities

• Analyze end-to-end processes for friction, bottlenecks, and failure points, using process mining, value-stream mapping, Lean Six Sigma, and root-cause analysis
• Assess process maturity, AI readiness, data availability and operational feasibility across business areas and build a prioritized portfolio based on value, feasibility, risk, and scalability
• Turn ambiguous business challenges into clear AI use cases with measurable outcomes

Design the future state

• Challenge established ways of working, policies, and process assumptions to identify opportunities to eliminate unnecessary work and fundamentally rethink how services and operations are delivered.
• Prototype and test future-state process concepts and workflows with business leaders and employees
• Design workflows that blend AI, automation, and human judgment, including decision rights, human-in-the-loop controls, and escalation paths
• Determine when AI is the right answer and when simpler automation or process simplification is more appropriate
• Define the future operating model: roles, responsibilities, decision rights, process controls, and workforce implication
• Write implementation-ready business requirements and acceptance criteria

Make it real

• Partner with engineering, product, data, security, and governance teams from process design through implementation and launch
• Lead process pilots, user acceptance, and operational readiness reviews
• Validate that implemented solutions reflect the intended future-state process, identifying gaps and driving resolution with business and technical teams.
• Work with change management and business leaders on training, communication, and adoption

Prove the value

• Set baselines and success metrics before launch, then track adoption, performance, and realized value
• Build business cases and benefits-realization plans with clear ownership
• Validate that improvements in productivity and released capacity translate into measurable business outcomes, such as increased throughput, reduced operating costs, improved service, or better customer and employee experiences.

Make every transformation easier than the last

• Turn what we learn in one business area into playbooks, frameworks, and standards that speed up the next one
• develop process transformation roadmaps and advise senior leaders on where AI can fundamentally change how work gets done
• Facilitate cross-functional workshops and coach teams to build AI capability across the organization