AI Delivery Product Manager: From Pilot to Production

McKinstry Company; Seattle (WA); On-site; USD 99,000 - 170,000; Full time

Benefits offered by this job

Competitive pay

401(k) with employer match

Paid time off

Medical, dental, vision coverage

Parental leave

Family formation benefits

Commuter benefits

Learning and advancement via McKinstry

Onsite gym / remote reimbursement

Job summary

McKinstry is seeking a Technical Product Manager for AI Delivery to turn AI strategy into shipped tools and measurable outcomes. You will own the intake, scoping, success metrics, and lifecycle from pilot to production, translating use cases into buildable requirements for AI engineering teams.

You will drive sprint execution, define acceptance criteria, data needs, and API specs, and manage pilots across multiple divisions. Strong agile experience and ROI focus are essential.

Qualifications

• Experience turning AI strategy into buildable product requirements.
• Ability to define success metrics for pilots and ROI.
• Knowledge of agile/sprint ceremonies and backlog governance.
• Ability to write clear acceptance criteria and data needs.

Responsibilities

• Own sprint methodology execution across all active AI tools and pilots.
• Translate approved use cases into product requirements and specs.
• Manage pilot intake, evaluation, scoring, and decision documentation.
• Own product lifecycle from pilot approval to production deployment.
• Maintain delivery metrics and pilot portfolio dashboards.

Skills

Product lifecycle

Agile delivery

Sprint planning

User stories

Acceptance criteria

Data requirements

API specs

AI product dev

ROI metrics

Stakeholder mgmt

Cross-functional work

Requirements writing

Education

CSPO

PMP

SAFe Product Owner

Job description

McKinstry is seeking a Technical Product Manager for AI Delivery to turn AI strategy into shipped tools and measurable outcomes. You will own the intake, scoping, success metrics, and lifecycle from pilot to production, translating use cases into buildable requirements for AI engineering teams.

You will drive sprint execution, define acceptance criteria, data needs, and API specs, and manage pilots across multiple divisions. Strong agile experience and ROI focus are essential.