AI Program Manager

This role reports to the Director of Technology. The AI Program Manager works through established governance and leadership channels and escalates policy, risk, budget, security, legal, vendor, or strategic decisions to the appropriate functional owner or governance body.

Governance and Program Operations

Coordinate AI Governance Committee agendas, review materials, decisions, action items, ownership, follow-up, and escalation tracking.

Maintain the firm-wide AI inventory, use-case register, decision log, exception log, AI-use records, and related program documentation needed for a defensible audit trail.

Operate the AI intake process as a practical front door for AI questions, tool requests, access requests, proposed use cases, pilots, and enablement needs.

Track AI program budget inputs, licensing utilization, spend requests, and business-case information for leadership review, while routing approval decisions to the appropriate owner.

AI Portfolio and Roadmap Coordination

Maintain visibility into AI initiatives, pilots, production solutions, tools, agents, automations, and supporting roadmaps across Reporting Centers and Shared Services.

Support prioritization discussions by helping evaluate business value, risk posture, feasibility, resource needs, timing, dependencies, and readiness.

Coordinate status reporting on initiative owners, milestones, dependencies, decisions, risks, lessons learned, and recommended next steps.

Prepare recommendations for leadership or governance review regarding which initiatives should continue, change, expand, pause, or retire.

Change Management and Communications

Communicate the why of AI, including benefits, limitations, guardrails, and the role of responsible adoption across the firm.

Support internal communications such as wins, FAQs, updates, user feedback, lessons learned, and approved-tool reminders.

Help manage adoption sentiment, address resistance, and support the culture shift required for new ways of working.

Strengthen the network of relationships and communities needed to sustain AI adoption over time.

Policy, Risk, and Responsible AI Support

Support implementation and communication of AI policy, the Six Prescriptions, operating guidance, data-handling expectations, and responsible-use practices.

Help employees understand approved-tool expectations, data classification requirements, human oversight, disclosure expectations, output accountability, and responsible use of AI-assisted work.

Coordinate reviews for higher-risk use cases, including HR, recruiting, public-facing content, sensitive data, business-system actions, autonomous or semi-autonomous agents, and AI-enabled workflows.

Monitor relevant AI governance and responsible-use developments and help keep guidance, training, and review materials current in partnership with the appropriate functional owners.

AI Solution Lifecycle and Pilot Coordination

Help teams frame AI opportunities, define the business problem, document expected outcomes, identify success measures, and prepare use cases for review.

Coordinate evaluation of proposed tools, prompts, agents, automations, integrations, and AI-enabled workflows with IT, Security, Risk Management, Data, and business stakeholders.

Track approved pilots, owners, timelines, outcomes, risks, lessons learned, and readiness for broader consideration.

Support lifecycle practices for review, testing, implementation readiness, monitoring, maintenance, documentation, and retirement of AI-enabled solutions.

Intake, Enablement, Training, and Adoption

Provide office hours, practical guidance, quick-reference materials, training coordination, and role-based enablement for onboarding and ongoing refresh.

Build trusted relationships with Reporting Center leaders, AI champions, Shared Services teams, and business stakeholders.

Promote approved AI tools and responsible-use expectations in a way that encourages voluntary adoption and makes governance feel helpful rather than punitive.

Capture user feedback, adoption barriers, common questions, and emerging needs, then translate them into improved guidance, communications, and reusable resources.

Tools, Platforms, and Vendor Review Coordination

Maintain approved-tool and vendor inventory information, platform documentation, review status, and related governance records.

Coordinate AI tool, vendor, platform, and buy-versus-build reviews using structured criteria for security, compliance, data protection, business value, cost, maintainability, capability, and stakeholder readiness.

Document evaluation outcomes, open questions, risks, dependencies, and recommendations for review by the appropriate decision makers.

Track emerging AI tools, market capabilities, and practical opportunities, then summarize relevant findings for governance and leadership review.

Data, Knowledge, Records, Prompts, and Agents

Partner with IT, Data, and business stakeholders to identify content that may be appropriate for AI-assisted search, reuse, summarization, or knowledge enablement.

Support consistent storage, discoverability, retention coordination, and ownership tracking for AI-generated artifacts, prompts, agents, decisions, and related records.

Partner with technical and business teams to help organize and maintain approved AI resources, including prompts, agents, guidance, and related documentation . Identify gaps, duplication, and opportunities to improve reusable AI resources across the firm.

Metrics, Value, and Leadership Reporting

Maintain program dashboards, adoption summaries, pilot status updates, training activity, utilization indicators, risk themes, and leadership-ready progress reports.

Track pilot outcomes, productivity indicators, cost impacts, participation, quality improvements, and realized benefits where measurable.

Identify duplication, common needs, adoption barriers, and opportunities to improve guidance, tools, training, or reusable resources.

Prepare decision-support materials for leadership regarding AI opportunities, risks, adoption trends, investments, readiness, and recommended next steps. Final decisions remain with the appropriate leadership or governance owner.

5+ years in program or project management, technology operations, governance, risk and compliance, business process improvement, change enablement, or a related field, ideally with exposure to AI, data, or emerging technology.

Experience standing up or operating cross-functional programs, committees, intake processes, governance workflows, or enterprise adoption programs.

Strong stakeholder management skills, with the ability to build trust and influence across technical and non-technical audiences, multiple offices, and decentralized teams.

A track record of translating policy, strategy, or ambiguous requirements into practical tools, processes, guidance, training, and reporting.

Working knowledge of AI governance, responsible-AI practices, data classification, human oversight, Microsoft 365 Copilot, AI-enabled workflows, or enterprise technology evaluation.

Excellent written and verbal communication skills, including experience developing or delivering training and creating practical resources, guidance, and leadership communications . Sound judgment balancing enablement with security, privacy, compliance, data protection, and business value considerations.

Highly organized and self-directed, with the ability to manage multiple workstreams, dependencies, stakeholders, and priorities with appropriate oversight.

Interest in change management, adoption enablement, and helping people use new tools safely and effectively.

Bachelor's degree or an equivalent combination of education and experience.

Stakeholders view the AI program as helpful, practical, and enabling rather than as a gatekeeping function.

AI initiatives, pilots, tools, vendors, agents, and decisions are visible, documented, and easier to coordinate across the firm.

Employees have clear guidance, training pathways, approved resources, and a practical front door for AI-related questions.

Pilot outcomes, adoption activity, risks, and value indicators are tracked consistently enough to support leadership decisions.

Higher-risk AI use cases are escalated to the appropriate owners before broader implementation.

Reusable prompts, agents, guidance, records, and lessons learned become easier to find, maintain, and improve.

This role may be performed remotely or from a KPFF office and is primarily desk-based knowledge work.

This role requires the ability to use a computer and standard office equipment for extended periods of time.

You may occasionally travel to KPFF offices, governance meetings, training sessions, or firm events.

You must be comfortable working in a fast-paced, evolving environment while managing multiple priorities and responding to changing needs.

KPFF is a collaborative, people-centered organization that values connection, curiosity, and long-term growth. In this role, you will help shape how the firm adopts one of the most significant technology shifts of our time responsibly, practically, and in a way that empowers our people.

If you enjoy building order out of ambiguity, supporting people, and turning strategy into everyday practice, we would love to hear from you.

This position is not eligible for visa sponsorship. Candidates must be authorized to work in the United States without sponsorship now or in the future.

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KPFF Consulting Engineers participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

KPFF Consulting Engineers is an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, creed, ethnicity, national origin, religion, marital status, sex/gender (including sexual orientation or gender identity), pregnancy, veteran status, citizenship status, physical or mental disability, or any other protected basis.