AI Pod Product Owner - Hybrid

AI Pod Product Owner - Hybrid

Level Required for Primary Skill   Expert (14+ years of experience - 10+ years of US experience mandatory)

Must Haves

• Bachelor’s degree in business administration, management information systems, computer science, or a related field
• Proven experience in product ownership or management within financial services, client onboarding, or customer relationship systems
• Broad and deep knowledge of financial services concepts, practices, and procedures, particularly in client onboarding or contact relationship systems
• Experience delivering data-driven or AI-enabled products in partnership with engineering and data science teams (for example: recommendations, decisioning, document intelligence, workflow automation, or generative AI assistants)
• Working knowledge of core AI/ML concepts (model training versus inference, features, drift, evaluation, and limitations) and ability to communicate trade-offs to non-technical stakeholders
• Ability to define and manage measurable success criteria for AI features (for example: precision/recall, quality scoring, latency, adoption, and human-review rates)
• Exceptional communication and interpersonal skills
• Demonstrated analytical ability and attention to detail
• Proven track record of leadership within matrixed teams, including task assignment, coaching, and mentoring
• Teamwork/collaboration mindset with a demonstrated ability to work with and influence stakeholders across functions
• Strong problem-solving skills and the ability to overcome ambiguity
• Prior experience with Agile methodologies and a robust understanding of the full software development lifecycle

Good to Have

• Advanced understanding of Product Management and Design Thinking principles and ability to expand these capabilities across teams
• Experience with generative AI (LLMs), prompt and workflow design, and evaluation approaches for quality, safety, and reliability
• Familiarity with MLOps practices and tooling (model deployment patterns, model registries, monitoring/alerting, and incident response)
• Experience partnering with risk, legal/compliance, privacy, and information security to meet model governance and regulatory expectations (for example: documentation, auditability, and controls)
• Experience in digital product ownership with exposure to high-performing teams and ongoing professional development of team members
• History of working on multi-disciplinary and cross-divisional product teams
• Experience guiding the management of resource needs, dependencies, and stakeholder solution requirements
• Demonstrated ability to advise and align with adjacent product teams to ensure consistent and cohesive delivery across products
• Background in building business cases and measuring delivery against defined success criteria

Key Responsibilities

• Align product strategy with execution, maintaining the product roadmap and prioritizing the body of work for current and future delivery
• Translate business problems into AI product epics and user stories with clear acceptance criteria, measurable outcomes, and defined human-in-the-loop decision points where needed
• Partner with data science, data engineering, and software engineering to prioritize data requirements, model development work, integration needs, and technical enablers
• Define and track AI product performance and quality metrics; drive continuous improvement through experimentation (for example: A/B tests), feedback loops, and monitoring
• Manage system plans and artifacts, ensuring timely delivery against resource, stakeholder, timeline, and milestone requirements
• Ensure responsible AI practices are embedded in delivery (for example: transparency, fairness considerations, privacy/security requirements, and appropriate use controls) in collaboration with relevant stakeholders
• Lead, coach, and develop a matrixed team in pursuit of the product vision and team member growth
• Advise and collaborate with other product teams to maintain a unified product strategy and progression