The Enterprise Artificial Intelligence Portfolio Manager leads the intake, prioritization, shaping, and value management of artificial intelligence initiatives across the enterprise. This role translates AI strategy and business demand into a prioritized, value-driven portfolio of opportunities that are clearly defined, aligned to business outcomes, and prepared for effective delivery.

The role sits at the intersection of business, operations, governance, and technology. It partners with senior business and operations leaders to clarify root problems, define desired outcomes, and shape practical AI-enabled opportunities. It also works closely with AI leadership, the AI Architect, AI Delivery leadership, data partners, governance stakeholders, and existing product teams to move AI ideas from initial demand signals into a disciplined, transparent portfolio.

This role helps Allied advance from traditional operating models that rely on complex rules-based systems, manual workarounds, and proportional headcount growth toward AI-enabled digital operating models that scale through intelligent systems, automation, human oversight, operational feedback, and continuous improvement. It provides the business framing, prioritization discipline, stakeholder alignment, delivery readiness, portfolio visibility, and value realization needed to ensure AI investments are purposeful, measurable, scalable, and aligned to organizational priorities.

Job Duties and Responsibilities:

Manage AI Intake, Portfolio Prioritization, and Sequencing – 30%

• Establish and manage  structured intake process to capture, evaluate, and prioritize AI opportunities across the enterprise.
• Assess  initiatives based on business value, strategic alignment, feasibility, risk, governance considerations, dependencies, delivery capacity, and readiness.
• Maintain portfolio visibility  into the AI opportunity pipeline, active initiatives, overlaps, tradeoffs, sequencing decisions, and portfolio health.
• Prepare portfolio recommendations and decision-support materials for AI leadership, AI Governance Committee., product leaders, and executive stakeholders.

Shape Business Problems into Delivery-Ready AI Opportunities – 25%

• Partner with senior business and operations leaders to move from broad AI requests or vague ideas to clearly defined problem statements, desired outcomes, target users, value hypotheses, and success metrics.
• Identify the root business or operational problem and ensure proposed AI initiatives are grounded in measurable business needs.
• Prepare prioritized opportunities for handoff to architecture and delivery teams, including scope, stakeholders, assumptions, dependencies, risks, expected outcomes, and initial future-state workflow considerations.
• Partner with the AI Architect, AI Delivery leadership, data partners, and business stakeholders to refine initiatives before proof of concept or execution planning begins.

Manage AI Portfolio Visibility and Value Realization – 20%

• Define and maintain portfolio-level measures for expected business outcomes, realized value, adoption, initiative status, and operational impact.
• Track value and outcome data from delivered AI initiatives to inform future prioritization, sequencing, and investment decisions.
• Communicate expected and realized value to AI leadership, governance stakeholders, product leaders, and executive audiences.
• Incorporate value, adoption, performance, and stakeholder feedback into recommendations about portfolio direction.

Integrate Governance, Risk, and Cross-Functional Alignment – 15%

• Ensure legal, risk, security, compliance, responsible AI, and governance considerations are reflected in initiative evaluation, prioritization, and delivery readiness.
• Partner with the AI Governance Lead, AI Governance Committee, Information Security, Legal, Risk, Compliance, business stakeholders, and delivery partners to support coordinated portfolio decisions.
• Surface gaps, dependencies, duplicate efforts, risks, and decision points requiring cross-functional alignment.
• Help coordinate a hybrid AI operating model across business, governance, product, data, architecture, and delivery stakeholders.

Advance AI Portfolio Management Maturity and Continuous Improvement – 10%

• Ensure legal, risk, security, compliance, responsible AI, and governance considerations are reflected in initiative evaluation, prioritization, and delivery readiness.
• Partner with the AI Governance Lead, AI Governance Committee, Information Security, Legal, Risk, Compliance, business stakeholders, and delivery partners to support coordinated portfolio decisions.
• Surface gaps, dependencies, duplicate efforts, risks, and decision points requiring cross-functional alignment.
• Help coordinate a hybrid AI operating model across business, governance, product, data, architecture, and delivery stakeholders.

Qualifications (Education, Experience, Certifications & KSA):

• Bachelor’s degree or equivalent combination of education and experience; master’s degree preferred.
• 8-10 years of work-related experience.
• Strong product and portfolio management fundamentals Experience structuring intake, prioritization, backlog management, portfolio visibility, and decision frameworks across multiple initiatives, value streams, or stakeholder groups.
• Ability to translate ambiguous business problems into clear opportunities Skilled at moving from broad AI requests or vague ideas to well-defined problem statements, desired outcomes, target users, success metrics, and value hypotheses.
• Stakeholder management and executive communication Comfortable working with senior business and operations leaders, facilitating alignment, and communicating priorities, tradeoffs, sequencing decisions, expected value, and realized outcomes clearly.
• Value framing and business case development Ability to define expected outcomes, quantify impact such as efficiency, cost, revenue, risk reduction, quality, customer experience, employee experience, scalability, or operational capacity, and articulate why initiatives matter.
• Practical AI literacy Working understanding of AI, machine learning, generative AI, intelligent automation, and emerging AI capabilities sufficient to evaluate opportunities, ask informed questions, assess feasibility at a high level, and partner effectively with technical teams.
• Cross-functional collaboration Ability to work effectively with AI leaders, AI architects, AI delivery teams, engineers, data teams, governance partners, existing product managers, and business stakeholders to move initiatives from idea to delivery readiness.

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The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. They are not intended to be an exhaustive list of all responsibilities, skills, efforts or working conditions associated with a job.

We offer our employees a robust compensation package! Our comprehensive benefits include: medical, dental and vision insurance coverage; 100% company-paid life and disability coverage, 401k options with company match, three weeks PTO by the end of the first year and much more. Allied proudly promotes from within as part of a strong commitment to providing career growth opportunities for employees of all levels. Our diverse business portfolio allows employees broad career options with the advantage of staying with the same organization.

All qualified candidates will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.

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