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Senior Program Manager, Automation and AI

McKinstry Company
$110,790.00 - $190,700.00 / yr
parental leave, paid time off, 401(k)
United States, Washington, Seattle
5005 3rd Avenue South (Show on map)
Oct 02, 2026

Build the future, spark innovation and align your career with purpose.

McKinstry is innovating the waste and climate harm out of the built environment and creating lasting impact. Together, we're building a thriving planet.

Buildings are a leading contributor to the climate crisis, generating nearly 40% of total global energy-related carbon emissions. We're making a lasting impact on our industry and within our communities by addressing the climate, affordability and equity crises through:

  • renewables and energy services
  • engineering and design
  • construction and facility services

To get where we're going, we need big thinkers, problem solvers and collaborative mindsets. Does that sound like you?

The Opportunity with McKinstry

McKinstry is looking for a Senior Program Manager - AI and Automation to join our Offsite Manufacturing division in Seattle, WA. The Senior Program Manager - AI and Automation owns the pipeline that converts emerging manufacturing automation and artificial intelligence capability into deployed, value-generating solutions for the business. The role discovers and maintains awareness of business needs across the business unit, researches and evaluates candidate technologies, builds the value proposition and business case, and proves solutions through structured pilots. Automation solutions are refined and coordinated with Manufacturing Engineering for implementation; AI applications are implemented by this role directly alongside the business function they affect. Additional responsibilities may include:

Business Need Discovery and Demand Management

  • Maintain a living, prioritized view of AI and automation opportunities across the business unit by interviewing leaders and embedding with production, engineering, supply chain, quality, project management, finance, and administrative teams as needed.

  • Conduct structured discovery (e.g. process observation, time and data studies, stakeholder interviews) to separate real constraints from symptoms and size the opportunity before any solution is proposed.

  • Translate business pain into problem statements and requirements that vendors, engineers, and internal stakeholders can act on.

  • Track the business unit's strategic plan, growth targets, and live production commitments so the technology pipeline is sequenced against what the business needs next, not against what is newest.

  • Work with Manufacturing Engineering to determine current bottlenecks in the production process, and seek out solutions that could increase throughput through use of AI and/or Automation.

Technology Research and Solution Evaluation

  • Scout and maintain a current, credible market view across manufacturing automation, to include robotics, material handling, machine vision, sensors, controls, and across enterprise and applied AI platforms, vendors, and integrators.

  • Run structured evaluations: requirements definition, RFI/RFP, vendor demonstrations, reference checks, technical feasibility assessment, and total cost of ownership.

  • Assess integration fit against existing systems of record (ERP, PLM, MES, document control) and coordinate with Enterprise IT, Data, Cybersecurity, and Legal on architecture, data handling, licensing, and security review.

  • Distinguish deployable capability from immature capability and report that distinction plainly, including when the recommendation is to wait or to do nothing.

  • Serve as the Modular Products representative to the Applied Frontier Technology team and enterprise technology teams - communicating the business unit's automation and AI roadmap, ingesting their recommendations and emerging-capability guidance, and feeding those inputs into the evaluation pipeline.

Value Proposition and Business Case

  • Build the business case for each candidate solution - quantified benefit, cost, payback, ROI, risk, resourcing, and the assumptions each depends on.

  • Establish baseline metrics before pilot so benefit claims are measurable after deployment rather than asserted.

  • Present recommendations and funding requests to business unit and enterprise leadership, and secure an accountable sponsor in the business function that will own the outcome.

  • Maintain the portfolio view of what sits in discovery, evaluation, pilot, implementation, and sustainment, and what each is worth.

Pilot Design, Execution, and Refinement

  • Design pilots with explicit hypotheses, success criteria, decision gates, budget, and a defined end date.

  • Lead pilot execution on the plant floor and within the business function, managing vendors, internal resources, schedule, and safety and quality risk.

  • Refine solution configuration, workflow, and supporting standard work based on pilot evidence, and iterate, scale, or terminate on that evidence.

  • Document pilot outcomes so the organization compounds what it learns.

Implementation and Adoption

  • Transition proven automation solutions to Manufacturing Engineering for execution - with complete requirements, vendor relationships, technical documentation, integration plan, and validated business case - while retaining accountability for the solution through installation, startup, and post-implementation support. Coordination with Manufacturing Engineering is a shared execution model, not a handoff of ownership: this role stays on the hook until the solution is running, adopted, and delivering the committed business case, and remains the escalation point for performance issues, rework, and optimization after go-live.

  • Own implementation of AI applications end to end alongside the impacted business function, covering data readiness, configuration, integration, testing, training, cutover, and hypercare.

  • Coordinate governance with Enterprise teams for deployed AI applications - data quality and access, model monitoring and drift, human review, and responsible-use guardrails aligned to enterprise policy.

  • Track realized benefit against the business case after deployment and report variance honestly.

Change Management and Capability Building

  • Build organizational readiness for automation and AI, addressing workforce impact, role change, and skills development directly and early rather than after deployment.

  • Train and coach production and business teams on deployed solutions so operating capability transfers to the team that owns the work.

  • Communicate the technology roadmap, pilot results, and realized value to mixed executive, engineering, operations, and craft audiences.

  • Report out to the Applied Frontier Technology team on pipeline progress, pilot outcomes, deployed solutions, and realized value, maintaining a two-way channel between Modular Products and enterprise frontier technology efforts.

What You Need To Succeed at McKinstry:

  • Bachelor's Degree required (industrial, mechanical, electrical, manufacturing, or computer engineering, computer science, or operations management preferred).

  • Minimum eight (8) years of team and/or program management experience required.

  • Demonstrated experience carrying technology from evaluation through pilot to production deployment in a manufacturing, industrialized construction, or offsite fabrication environment.

  • Working knowledge of manufacturing automation technologies such as industrial robotics, automated material handling, machine vision, sensors, and PLC/controls integration.

  • Working knowledge of applied artificial intelligence and machine learning, including a practical understanding of where current capability performs reliably and where it does not.

  • Demonstrated ability to build and defend a quantified business case, including benefit modeling, ROI, payback, and total cost of ownership.

  • Working knowledge of process mapping and lean methods - standard work, kaizen, A3 problem solving, root cause analysis.

  • Demonstrated ability to collaborate with and influence people at all levels across the organization required.

  • Excellent facilitation skills and the ability to lead diverse, cross-functional project teams required.

  • Ability to operate effectively in a high-growth environment where technology strategy is authored in parallel with live production commitments.

  • Strongly Preferred: vendor, integrator, and capital equipment procurement experience; data platform and integration fundamentals (APIs, data pipelines, structured and unstructured data); AI governance, security, and privacy practice; PMI certification; LEAN Construction; engineer-to-order or high-mix production experience.

PeopleFirst Benefits

When it comes to the basics, we have you covered:

  • Competitive pay
  • 401(k) with employer match and profit-sharing plan
  • Paid time off and holidays
  • Comprehensive medical, prescription, dental, and vision with low or zero deductible options and low out of pocket maximums

People come first at McKinstry, and we go beyond the basic benefits with:

  • Family formation benefits, including adoption and IVF assistance
  • Up to 16 weeks paid parental leave
  • Transgender inclusive benefits
  • Commuter benefits
  • Pet insurance
  • "Building Good" paid community service time
  • Learning and advancement opportunities via McKinstry University
  • McKinstry Moves onsite gyms or reimbursement for remote workers

See benefit plan documents for complete details.

If you're driven by our vision to build a thriving planet together, McKinstry is the place to build your career.

The pay range for this position is $110,790 - $190,700 per year; however, base pay offered may vary depending on job-related knowledge, skills, and experience. A bonus may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. Base pay information is based on market location.

The McKinstry group of companies are equal opportunity employers. We are committed to providing equal employment opportunities to all employees and qualified applicants without regard to sex, gender identity, sexual orientation, age, race, color, creed, marital status, national origin, disability, veteran status, genetic information or any other basis protected by law. This policy applies to all terms and conditions of employment including, but not limited to employment, advancement, assignment, and training. This commitment to Equal Employment Opportunity is made equally as a social responsibility and as an economic and business necessity.

McKinstry is a drug-free workplace. Employment iscontingent upon successfully passing a pre-employment drug and alcohol test, complying with the requirements of the Immigration Reform and Control Act and a Confidentiality Agreement, in addition to successful outcomes of background and reference checks.

Applicants for this role will only be considered if they possess current US Work Authorization, and do not require employer-sponsored VISA support to begin or remain in this role.

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