AI Product and Portfolio Manager; On-Site

The Artificial Intelligence Product and 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.

• 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.

• 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.

• 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.

• 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.