AI Governance Product Manager

RTX•New York, NY

3d•$132,400 - $251,600•Remote

About The Position

The Senior Manager, AI Governance Product Lead is a strategic leader responsible for shaping, delivering, and operationalizing governance capabilities that ensure trustworthy data and responsible AI across the enterprise. In this role, you will partner closely with the Director of Data Governance & AI Governance to translate governance frameworks, regulatory expectations, and risk controls into scalable products, platforms, and operating models. You will drive alignment across business, technology, data, risk, and compliance stakeholders to ensure the organization can safely accelerate its use of data and artificial intelligence. This position requires deep domain understanding of emerging AI governance practices such as model risk management, transparency, and lifecycle controls. You will guide discovery, define product vision, prioritize features, and oversee execution of core governance capabilities—such as policy automation, metadata platforms, lineage, quality monitoring, model registries, and responsible AI controls. Your work will be foundational to building enterprise trust, ensuring regulatory readiness, and scaling the organization’s AI ambitions responsibly.

Requirements

Typically requires: A University Degree or equivalent experience and minimum 10 years prior relevant experience, or An Advanced Degree in a related field and minimum 7 years experience
8+ years of experience in product management, data governance, analytics platforms, or AI/ML governance, including leadership of cross-functional initiatives.
5+ years experience in data platforms, governance tools, or enterprise AI capabilities.
5+ years working with AI/ML model lifecycle, including AI governance, risk assessments, transparency documentation, and monitoring practices.
Experience translating legal, regulatory, and risk requirements into product features, workflows, and control checkpoints.
5+ years experience in Agile delivery, backlog management, and writing clear epics, features, and user stories.

Nice To Haves

Master’s degree in Business, Information Systems, Data Science, or a related field preferred
Experience supporting enterprise-level AI Governance programs.
Background in regulated industries (financial services, healthcare, insurance, life sciences, energy).
Certifications such as Responsible AI certifications, or SAFe Product Owner/Product Manager.
Experience with model risk management, AI audit frameworks, or regulatory guidelines (NIST AI RMF, EU AI Act concepts, OCC/FRB guidance).
Experience driving operating model transformations or governance process redesign.
Outstanding collaboration and influence skills across technical and non-technical stakeholders.
Familiarity with tools such as Collibra, Alation, Informatica, Monte Carlo, Databricks, MLflow, or AI governance platforms.
Strong communication skills and the ability to simplify complex governance concepts for diverse audiences.
Experience delivering enterprise data products or governance capabilities at scale.

Responsibilities

Define AI Governance Strategy & Roadmap: Develop and maintain a multi-year strategy for AI Governance platforms, aligning with enterprise risk, compliance, data strategy, and in alignment with Product AI Governance.
Coordinate & Lead team to roadmap and delivery targets: Drive alignment around key milestones, orchestrate cross functional coordination, and proactively remove blockers to ensure the team can deliver iterative, high value capabilities.
Translate Governance Requirements into Platform Capabilities: Convert policies, standards, and control requirements into actionable feature sets, user stories, and workflows across data and AI domains within the platform.
Discovery & Stakeholder Alignment: Structured discovery with Legal, Compliance, Risk, Data Engineering, and business teams to address governance needs.
Advise on Governance Operating Models: Support the maturation of AI governance processes and federated governance structures.
Delivery across AI Governance capabilities: Oversee development of capabilities such as AI model registries, AI use case registry and risk assessment tools, incident management, and monitoring workflows.
Regulatory & Control Compliance: Collaborate with Risk, Compliance, Legal, and Internal Audit to ensure RTX meet regulatory requirements (e.g., AI regulations, GCP-60).
Champion Responsible AI: Embed fairness, transparency, explainability, and ethical guidelines into AI lifecycle tools and processes.
Enable Business Adoption: Support training, communications, change management, and rollout strategies to onboard user and teams.
Manage Risk & Prioritization: Identify and manage risk associated with AI use cases
Mentor & Elevate the Team: Provide guidance to analysts, product managers, and governance SMEs; help uplift skills, tool proficiency, and governance maturity across the organization.
Create and maintain playbooks for model evaluations, bias testing, privacy assessments, and production monitoring with clear thresholds/SLA triggers.
Drive change management: training, communications, and adoption strategies to embed responsible AI practices across business units.