Portfolio Manager Jobs

About The Position

Requirements

• Bachelor’s degree or equivalent combination of education and experience
• 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.

Nice To Haves

• Master’s degree preferred

Responsibilities

• Establish and manage a 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.
• 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.

Benefits

• 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