Director, Product Management Operations & AI Enablement - Capital One Software (Remote)

Capital One•Richmond, VA

2d•Remote

About The Position

Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry. Capital One is a digital-first financial institution that has successfully productized its technology DNA into a standalone, enterprise B2B SaaS business division. Capital One Software commercializes the battle-tested, cloud-native tools built in-house—such as Slingshot (for Snowflake optimization) and Databolt (for advanced data security and AI enablement)—to help other Fortune 500 companies accelerate their cloud, data, and AI journeys. This unique, software-centric identity is embedded deeply across the enterprise, inspiring us to build and deploy internal platform tools with the same rigor, scalability, and commercial mindset as our outward-facing products. The Product Operations team sits at the critical intersection of product strategy, engineering execution, and organizational design. Our mission is to eliminate process overhead, build the infrastructure for data-driven decisions, and empower product managers to maximize shipping velocity and business outcomes. Central to this mission is driving the adoption, integration, and operational deployment of our advanced internal and external AI toolkit across our newly formed AI Native Pods. As the leader of this team, you will not be product-managing the underlying software tools themselves; instead, you will lead the team responsible for figuring out how best to deploy our internal and external AI toolkit across the enterprise to maximize business outcomes, and developing the optimal roles and responsibilities of AI Native Pod members. You will architect the next generation of our Product Development Life Cycle (PDLC), leading a substantial paradigm shift: evolving our delivery organization from traditional, legacy Agile methodologies into an AI-Native Software Development Lifecycle (SDLC). You and the team will optimize every step in the process from Discovery to Roadmap Planning to Release Management. In this role, you’ll be expected to leverage your team to demonstrate mastery across Capital One’s five core product pillars: Human Centered: Obsesses over internal product managers and engineers as your target customers, ensuring AI tools are deployed in ways that genuinely remove friction rather than adding administrative burden. Business Focused: Drives portfolio leverage, resource forecasting, and execution excellence to ensure AI tooling adoption directly translates to accelerated business outcomes and speed-to-value. Technology Driven: Champions the deployment of enterprise AI enablement tools, automation, and agentification frameworks to drive measurable productivity gains across the organization. Integrated Problem Solving: Identifies and resolves complex cross-functional bottlenecks with a pragmatic, non-dogmatic approach to dismantling outdated delivery frameworks. Transformational Leadership: Influences senior business, technical, and risk leaders to align around modern operating rhythms and adopt an AI-Native culture.

Requirements

Bachelor's degree in any field and 5 years of Product Management experience
Proven success leading the rollout, change management, and scaled adoption of large enterprise software platforms, developer tools, or enterprise-wide Agile/DevOps transformations.
Deep familiarity with emerging AI tool chains, developer agents, and LLM capabilities. Experience scaling internal AI productivity tools
Strong structural understanding of traditional product frameworks (Scrum, Lean, Design Thinking) paired with a highly pragmatic approach to automating or dismantling them.
Exceptional communication skills with a demonstrated ability to partner with and influence VPs of Product, Engineering Directors, and senior risk leaders without direct authority.

Responsibilities

Streamline Intake & Prioritization: Standardize frameworks for cross-functional requirements gathering, portfolio investment trade-offs, and strategic planning cycles.
Eliminate Operational Friction: Audit existing Agile/Scrum overhead, systematically removing non-value-add meetings and administrative roadblocks so product managers can focus on customer discovery and strategy.
Cross-Functional Connective Tissue: Align Product, Engineering, Design, Risk/Legal, and Go-To-Market (GTM) teams around unified operating rhythms and clear stakeholder communication streams.
Transform the SDLC: Redesign and mature the end-to-end Product Lifecycle Management (PLM) and SDLC frameworks, moving teams from rigid, sprint-based execution to continuous, AI-accelerated delivery workflows.
Orchestrate AI Tooling Adoption: Lead the enterprise-wide operational strategy, rollout, and scaling of our core internal AI platform and third-party AI enablement capabilities (e.g., automated PRD creation, AI-assisted roadmapping, synthetic user testing, and AI-driven release documentation).
Define "Agentification" Playbooks: Partner with engineering leadership to build the frameworks and playbooks required to integrate AI agents into daily team routines, requirements intake, backlog governance, and quality management.
Build AI Fluency: Establish a Product Center of Excellence to upskill product teams in AI literacy, prompt engineering, and responsible AI guardrails, ensuring organizational readiness.
Process Insights Infrastructure: Manage the product operations tooling stack (Jira, LogRocket, etc.) to enable the team to complete AI-Native workflows with optimal efficiency.
Outcome-Based KPIs: Establish and monitor, in partnership with the Data & Analytics team, organizational metrics beyond pure delivery velocity to additional business outcomes, tracking how AI-Native development impacts all aspects of the value chain.