Platform Product Manager

Ally•Charlotte, NC

3d•$110,000 - $180,000

About The Position

The Manager, Product Management – Enterprise Data & AI Platforms defines and delivers the product strategy and multi-quarter roadmap for Ally’s shared GenAI, machine learning, data, and knowledge platform. The role owns developer-facing capabilities—including AI gateways, agent frameworks and templates, model and capability registries, evaluation tools, and reliability dashboards—and translates business workload needs into reusable, secure, governed, SLA-backed platform products. Reporting to the Head of the Data & AI Platform team, the manager partners with engineering, FinOps, Enterprise Architecture, Model Risk Management, governance leaders, and senior leadership to align platform investments with enterprise priorities, delivery-team demand, and measurable outcomes. The platform supports capabilities across Data Foundation, Knowledge Platform, Catalog & Governance, Model Platform, Apps & Agents, AI Reliability, and Platform Fabric. The role manages product prioritization, versioning, adoption, reliability, and cost metrics. It turns workload requests into platform features, reusable paved-path patterns, or explicit non-goals; owns product versioning, SLAs, deprecation policies, and paved-path contracts; and measures adoption, reliability, and cost-to-serve. The manager also champions reusable platform products and works to make the paved path safer and less costly than bespoke alternatives. The ideal candidate brings substantial product management and hands-on AI/ML experience, knowledge of modern AI platforms and responsible AI, and the ability to lead technical trade-off discussions in a regulated financial-services environment.

Requirements

Bachelor of Science and 10+ years of combined experience across product management and hands-on ML, GenAI, or data/AI engineering, or an equivalent combination of education and experience.
At least 5 years of product management experience owning developer-facing, platform, or internal PaaS products, with demonstrated ownership of versioned APIs, SLA contracts, and deprecation policies at enterprise scale.
At least 3 years of hands-on ML, GenAI, or applied AI practitioner experience; must have shipped AI systems into production and be able to reason about model evaluation, retrieval quality, prompt and agent design, drift, and inference cost.
Experience defining and delivering GenAI and ML platform roadmaps, including model hosting and inference gateways, agent frameworks, retrieval-augmented generation, evaluation harnesses, prompt and model registries, and continuous monitoring.
Familiarity with modern AI platforms such as Amazon Bedrock, SageMaker, and Azure OpenAI, and ability to lead architectural trade-off discussions with senior engineers.
Understanding of the AI Development Life Cycle for classical ML and GenAI/agent systems and ability to map platform capabilities to lifecycle stages.
Ability to translate AI use cases into measurable business outcomes and publish monthly platform scorecards for senior leadership.
Knowledge of responsible AI, model governance, model risk management partnership, human-in-the-loop controls, auditability, and continuous monitoring for drift, bias, hallucination, and prompt-injection risk.
Comfort operating alongside second-line functions in a regulated financial-services environment.
Strong Agile product leadership using Scrum or Kanban and ability to lead complex, cross-team platform initiatives with predictable execution.
Excellent written and verbal communication, including presenting technical trade-offs clearly to engineering and executive audiences.
Minimum qualifications also state 7+ years of relevant experience and a bachelor’s degree in a relevant field of study or equivalent.

Nice To Haves

Advanced degree in Computer Science, Engineering, Data Science, or a related field.
Background in an AI platform organization at a bank, insurer, or health payer.
Prior contribution to or evaluation of production model gateways, agent frameworks, or evaluation harnesses.

Responsibilities

Define and publish a rolling, multi-quarter product roadmap sequenced by workload demand and aligned with enterprise priorities.
Own GenAI and ML platform product roadmaps, including the AI Gateway, agent development tools and templates, capability and model-risk registries, and AI evaluation and monitoring dashboards.
Translate business workload needs and requests into platform features, reusable paved-path patterns, or explicit non-goals.
Own product versioning, service-level agreements, deprecation policies, and paved-path contracts.
Manage product prioritization, adoption, reliability, and cost metrics.
Partner with FinOps and Model Platform engineering to measure unit economics, including cost per inference, GPU utilization, and cost per agent run.
Represent EDA Platforms in Enterprise Architecture and Model Risk Management forums, presenting options, trade-offs, and recommendations.
Instrument products with adoption, reliability, and cost-to-serve telemetry and provide platform-health visibility to executives.
Package recurring workload patterns into reusable products and promote adoption of the platform’s paved paths.
Partner with engineering and governance delivery leaders to prioritize, sequence, and evolve platform capabilities.
Drive cross-team platform initiatives across engineering pods, vendor partners, and governance stakeholders.
Translate AI use cases into measurable business outcomes and publish monthly platform scorecards for senior leadership.
Apply responsible AI practices, including governance, human-in-the-loop controls, auditability, and monitoring for drift, bias, hallucination, and prompt-injection risk.

Benefits

Market-competitive base pay and pay-for-performance incentives through an annual incentive plan.
At least 20 paid time-off days, 11 paid holidays, and 8 hours of annual volunteer time off; time off is prorated and programs vary by employment status and management level.
401(k) retirement savings plan with matching and company contributions.
Student loan pay-down and 529 educational savings assistance programs.
Tuition reimbursement.
Employee stock purchase plan.
Financial learning center and financial coach access.
Medical, dental, and vision insurance options.
Employee, spouse, and child life insurance.
Short- and long-term disability insurance.
Health Savings Account with employer contributions and Healthcare FSA.
Critical illness, accident, and hospital indemnity insurance.
Total well-being program supporting physical, social, emotional, and financial well-being.
Adoption, surrogacy, and fertility assistance.
Paid parental and caregiver leave.
Dependent Day Care FSA, backup child and adult/elder care days, and childcare discounts.
Employee Assistance Program.
Subsidized and discounted Weight Watchers program and other employee discount programs.
Depending on the role, travel allowances, relocation assistance, signing bonus, and/or equity may be available.