Senior AI Product Owner

Ascensus•Newton, PA

4d•$120,000 - $160,000

About The Position

Ascensus is the leading independent technology and service platform powering savings plans across America, providing products and expertise that help nearly 16 million people save for a better today and tomorrow. Position Summary As a Senior Product Owner, Enterprise AI Platform, you will define, prioritize, and drive execution of platform capabilities that turn modern AI technology into practical, reliable, and measurable business value. This role provides product ownership and delivery leadership across multiple scrum teams. You will partner closely with: Software Engineers, SDETs, DevOps Engineers, Support Engineers, Architects, Product leaders, AI specialists, Business stakeholders, Operational leaders. This is a senior product ownership role for someone who can balance business outcomes, user needs, technical complexity, delivery execution, responsible AI adoption, and team effectiveness. You will be responsible for: Defining and maintaining the roadmap for Enterprise AI Platform capabilities, Prioritizing team backlogs based on business value, user impact, risk, dependencies, and platform strategy, Translating business needs into clear epics, features, user stories, acceptance criteria, and measurable outcomes, Representing users, internal customers, and stakeholders throughout planning, delivery, validation, and release, Partnering with engineering, architecture, AI, support, operations, and business teams to deliver production-grade AI capabilities, Staying informed on emerging AI tools, models, workflows, and platform patterns, Partnering with technical teams to shape demos, POCs, pilots, and early concepts that validate value before larger investment, Helping teams operate effectively by applying Agile practices pragmatically, not performatively. This role requires an AI product builder mindset: the ability to combine product ownership, user experience thinking, technical curiosity, and AI-assisted prototyping to help teams validate ideas quickly and focus on the highest-value opportunities. The Senior Product Owner should be comfortable using demos, workflow sketches, lightweight prototypes, user feedback, and production data to shape product direction before larger engineering investment is made. AI prototyping is increasingly becoming part of modern product discovery because product leaders can use AI tools to turn PRDs, sketches, and designs into working prototypes faster than traditional handoff cycles.

Requirements

7+ years of professional experience in product ownership, product management, business analysis, technology delivery, software engineering, quality engineering, or a related field.
4+ years of experience as a Product Owner, Product Manager, Business Analyst, or similar role supporting software delivery teams.
Experience providing product ownership or delivery leadership across multiple scrum teams, products, workstreams, or complex initiatives.
Experience owning or supporting product roadmaps, team backlogs, feature prioritization, sprint planning, and release planning.
Experience translating business needs into clear epics, features, user stories, acceptance criteria, and measurable outcomes.
Strong understanding of Agile delivery practices and modern software development life cycle practices.
Ability to apply Agile practices pragmatically, using planning, refinement, reviews, retrospectives, and team coordination when they improve delivery, alignment, or continuous improvement.
Experience working closely with software delivery teams that include: Software Engineers, SDETs, DevOps Engineers, Support Engineers, Quality Engineers
Ability to prioritize work based on business value, user impact, technical risk, dependencies, and delivery capacity.
Experience supporting user acceptance testing, release readiness, product validation, and feedback loops.
Ability to use product discovery techniques, lightweight prototypes, demos, workflow diagrams, or AI-assisted tools to validate user needs and improve stakeholder alignment.
Strong communication, facilitation, negotiation, conflict resolution, and stakeholder management skills.
Strong analytical skills with the ability to use data, feedback, and KPIs to guide product decisions.
Ability to create clarity in ambiguous or fast-changing environments.
Demonstrated curiosity and ability to learn quickly in a fast-evolving technical environment.
Bachelor’s degree in Business, Computer Science, Computer Information Systems, Business Information Systems, a related field, or equivalent practical experience.

Nice To Haves

Product ownership for enterprise platforms, internal developer platforms, AI platforms, shared services, or internal business applications
AI-enabled applications, LLM-powered systems, RAG, chatbots, agent workflows, prompt strategies, or AI-assisted engineering practices
Azure, Azure AI Foundry, Azure DevOps, Aha!, Miro, or similar tools
Writing behavior-driven development, or BDD, scenarios and acceptance criteria
Automated testing, SDET practices, Playwright, Python-based test automation, or end-to-end testing
CI/CD, release automation, production readiness, incident trends, or operational improvement
Observability, product analytics, telemetry, user feedback, or operational metrics
Enterprise systems such as Salesforce, internal platforms, APIs, workflow systems, or service-oriented architectures
Organizational readiness, change management, training, adoption planning, or support enablement
Coordinating product direction, backlog alignment, and dependencies across multiple scrum teams
Shaping or evaluating AI-related demos, POCs, pilots, prototypes, or early-stage product concepts
Turning discovery learnings, stakeholder feedback, and pilot outcomes into product roadmap decisions
Facilitating Agile team activities, delivery health conversations, retrospectives, dependency resolution, or continuous improvement efforts
Coaching or mentoring other Product Owners, Business Analysts, or Scrum Team members

Responsibilities

Defining and maintaining the roadmap for Enterprise AI Platform capabilities
Prioritizing team backlogs based on business value, user impact, risk, dependencies, and platform strategy
Translating business needs into clear epics, features, user stories, acceptance criteria, and measurable outcomes
Representing users, internal customers, and stakeholders throughout planning, delivery, validation, and release
Partnering with engineering, architecture, AI, support, operations, and business teams to deliver production-grade AI capabilities
Staying informed on emerging AI tools, models, workflows, and platform patterns
Partnering with technical teams to shape demos, POCs, pilots, and early concepts that validate value before larger investment
Helping teams operate effectively by applying Agile practices pragmatically, not performatively
Build and maintain a clear, prioritized roadmap for Enterprise AI Platform capabilities.
Keep multiple team backlogs healthy, actionable, and aligned to business and platform priorities.
Translate ambiguous business needs into clear, sprint-ready work.
Help teams deliver high-quality AI-enabled capabilities consistently.
Make practical prioritization decisions when demand exceeds capacity.
Use KPIs, user feedback, production data, and business outcomes to guide product decisions.
Stay curious about emerging AI technologies and identify where they can create practical value.
Use demos, pilots, POCs, prototypes, and early experiments to validate ideas before scaling investment.
Blend product judgment, user experience thinking, and technical curiosity to identify which AI opportunities are worth pursuing.
Help stakeholders understand what teams are building, why it matters, and how it improves real business outcomes.
Apply Agile Scrum practices with the right level of structure for each team, avoiding unnecessary process overhead.
Facilitate team and cross-team conversations when needed to improve clarity, remove blockers, resolve dependencies, and increase delivery effectiveness.
Raise the quality of product ownership and Agile delivery practices across the teams.
Help connect day-to-day execution to broader Enterprise AI Platform goals.
Grow your own product leadership scope, judgment, and organizational influence over time.