AI Program Manager

Job Description

Job Description

We have been engaged on a search for a supply chain and distribution client that is building out an enterprise AI program focused on identifying, prioritizing, and delivering high-value AI use cases across the business. The company operates in a practical, operations-heavy environment where AI can be applied to supply chain, distribution, customer service, product, process, productivity, and workflow challenges.

This is a high-visibility opportunity for a hands-on AI Program Manager who can help move an enterprise AI program from approved strategy into disciplined execution. The organization has already created the initial strategy and framework, but the program is still early in maturity and needs someone who can bring structure, governance, prioritization, delivery discipline, and business-facing leadership.

This is not a pure AI strategy role, and it is not a traditional IT Project Manager role. The company needs someone who can help identify real AI opportunities, prioritize the right use cases, build practical governance, and personally drive approved initiatives through execution and adoption.

This is a contract-to-hire opportunity. The role is remote-friendly, with local or hybrid availability near Malvern, PA preferred but not required.

The Role You'll Play

The AI Program Manager will help own and drive the company's enterprise AI program. This is the framework and governance model used to identify, evaluate, prioritize, justify, and deliver AI opportunities across the organization.

This person will work closely with IT leadership, the PMO, business stakeholders, security, architecture, technical teams, vendors, and executive leadership. They will help business teams bring forward AI opportunities, determine whether those opportunities are practical and valuable, score and prioritize them, prepare business justification, and then drive approved projects through execution.

This is a hands-on program leadership role. The AI Program Manager will not simply facilitate meetings or maintain a roadmap. Once use cases are approved, this person will be expected to coordinate resources, manage workstreams, track risks and dependencies, drive decisions, and keep projects moving through launch and adoption.

Responsibilities include:

• Own and drive the enterprise AI program from use case intake through prioritization, approval, execution, launch, and adoption.

• Develop and mature the program's governance model, including scorecards, intake processes, prioritization tools, SOPs, value tracking, and repeatable ways of working.

• Work with business teams to identify AI opportunities, clarify business problems, define use cases, and determine whether AI is the right solution.

• Help evaluate, rank, and justify AI initiatives before they are presented to executive leadership for approval.

• Partner with the CIO, CFO, CEO, and other executive stakeholders by presenting clear business rationale, expected value, risks, dependencies, resource needs, and tradeoffs.

• Drive approved AI initiatives through delivery by coordinating business analysts, solution architects, developers, testing teams, vendors, and internal resources.

• Manage project scope, schedule, budget, resources, risks, dependencies, communication, adoption, and delivery quality.

• Ensure AI-related tools, agents, platforms, and internal capabilities are not launched in a “wild west” manner.

• Partner with security, architecture, IT, business stakeholders, and leadership to ensure appropriate governance, communication, risk review, and adoption planning are in place before broader rollout.

• Evaluate build-vs-buy options for AI initiatives, including internal resource needs, vendor options, cost, timing, delivery risk, and speed-to-value.

• Help determine whether initiatives should be built internally, sourced externally, or handled through a hybrid model.

• Support AI pilots, proofs of concept, production deployments, internal AI agents, automation tools, analytics solutions, and post-launch support.

• Translate operational business needs into practical AI-ready opportunities with measurable success metrics such as savings, ROI, adoption, productivity, cost reduction, performance improvement, or operational efficiency.

• Apply Agile, Waterfall, or hybrid delivery approaches depending on project needs.

• Facilitate workshops, stakeholder meetings, executive updates, steering discussions, and project reviews.

• Challenge unrealistic assumptions and guide business partners toward feasible, measurable, governed, and useful AI solutions.

• Help mature the PMO's role as a strategic advisor to the business.

Background Profile:

The ideal candidate is a hands-on AI Program Manager who can help own and drive an enterprise AI program from use case intake through prioritization, approval, execution, launch, and adoption. This is not a traditional IT Project Manager role, and it is not a pure AI strategy role. The company needs someone who can bring practical program structure, business-facing leadership, and delivery discipline to a growing AI program that is still early in maturity.

The strongest candidates will have experience implementing AI, automation, analytics, machine learning, or data-driven solutions in a business environment. They should understand how to work with business leaders to identify operational pain points, assess whether AI is the right solution, define business value, prioritize opportunities, and move approved initiatives into execution.

Manufacturing, distribution, supply chain, logistics, or operational workflow experience is strongly preferred. Many of the expected AI opportunities will come from supply chain and operations, so this person needs enough domain understanding to engage business stakeholders around workflows, bottlenecks, handoffs, data dependencies, resource constraints, and practical use cases such as PO expediting, de-expediting, transfers, inventory movement, operational planning, productivity improvement, and process automation.

This person does not need to be an AI engineer or hands-on developer. However, they must have enough technical fluency to understand AI solution options, ask good questions, evaluate feasibility, and communicate clearly with IT, vendors, business leaders, and executives. Strong soft skills and executive communication are critical, especially when explaining why one use case should be prioritized over another and what value, savings, risks, resources, or tradeoffs are involved.

More specifically:

• 7 to 10 years of experience leading cross-functional technology, AI, automation, analytics, digital transformation, PMO, or business process improvement initiatives.

• Proven experience implementing AI, machine learning, automation, analytics, or data-driven solutions in a business environment.

• Experience managing multiple related initiatives or workstreams, including intake, prioritization, planning, execution, risk management, dependency tracking, stakeholder communication, launch, and adoption.

• Ability to help define AI use cases, clarify business problems, assess feasibility, and establish success metrics tied to savings, ROI, adoption, productivity, cost reduction, performance, or operational improvement.

• Experience supporting or building governance, scorecards, intake models, SOPs, prioritization frameworks, roadmap planning, or value-tracking processes.

• Experience coordinating business stakeholders, IT teams, business analysts, solution architects, developers, testing teams, vendors, and third-party partners.

• Strong understanding of manufacturing, distribution, supply chain, logistics, foodservice, packaging, or other operationally intensive business environments strongly preferred.

• Ability to translate business needs into practical AI-ready opportunities without overcomplicating the process.

• Ability to evaluate build-vs-buy options, internal resource needs, vendor involvement, timing, cost, and speed-to-value tradeoffs.

• Strong executive communication, stakeholder facilitation, workshop leadership, and business relationship management skills.

• Ability to challenge unrealistic assumptions, push back diplomatically, and guide stakeholders toward solutions that are feasible, measurable, governed, and useful.

• Comfortable being both strategic and hands-on, including building plans, documenting decisions, tracking risks, driving follow-ups, managing dependencies, and keeping momentum across the program.

• Working knowledge of Agile, Waterfall, and hybrid delivery approaches.

Preferred background:

• Experience in manufacturing, distribution, supply chain, logistics, foodservice, packaging, or similar operational environments.

• Experience with Microsoft AI tools such as Copilot, Copilot Studio, Microsoft Foundry, Azure AI, Power Platform, MCP-related capabilities, or related Microsoft technologies.

• Experience managing AI pilots, proofs of concept, internal AI agents, automation tools, analytics solutions, or production AI deployments.

• Experience creating or supporting AI adoption roadmaps, governance models, steering updates, scoring tools, SOPs, and value-tracking dashboards.

• AI, machine learning, data analytics, automation, or related training/certification.

• Experience presenting program health, risks, dependencies, decisions needed, resource tradeoffs, and value delivered to CIO, CFO, CEO, or executive stakeholders.

• PMP certification or active pursuit preferred.

• Agile certification such as Scrum or SAFe preferred.