Staff Product Manager, Docker

• 10+ years of product management experience, with 4+ years at Staff level or above
• Proven track record building and scaling platform, infrastructure, or developer-tooling products that enable other teams or developers at high-growth technology companies
• Strong technical acumen: able to engage credibly in architecture and trade-off discussions across Kubernetes, CI/CD, networking, APIs, and observability
• Deep understanding of platform-as-a-product principles: self-service, golden paths, developer experience, adoption over mandate, and internal customer success
• Fluency with where AI and agentic workflows are heading, including hands-on familiarity with LLM-powered tooling or AI agents, and good judgment about where automation belongs
• Excellent stakeholder management and the ability to influence without authority across a technical organization
• Strategic thinking that balances long-term platform vision with near-term team needs and business objectives
• Clear written and verbal communication suited to a remote-first environment

Desirable

• Docker is seeking a Staff Product Manager to own product strategy across the Infrastructure and AI Dev Tools organization: the foundation that hundreds of Docker engineers build on, and an increasingly important source of the AI-native capabilities we bring to customers
• This is a rare role that sits at the seam between Docker's internal developer platform and the customer-facing products that grow out of it
• The Infrastructure team builds and operates the cloud-native platform behind products like Docker Hub, Gordon, and AI Governance: multi-tenant Kubernetes, multi-region networking, self-service provisioning, observability, and the paved roads that let teams ship safely without re-solving the same problems
• The AI Dev Tools team builds the agents and tooling that are modernizing how software gets designed, built, shipped, and operated, both for Docker's own engineers and, increasingly, for the developers and enterprises who rely on Docker
• You will treat the platform as a product. That means driving clarity on prioritization, defining golden paths, measuring adoption rather than mandating it, and earning the trust of internal teams the same way a great product earns the trust of customers
• It also means spotting which internal tools and platform capabilities are ready to become customer-facing offerings, and shaping that path from prototype to product
• You will work closely with engineering leaders, principal and staff engineers, Security, and the product teams across Docker, as well as with customers as internal tools graduate into products
• What Would Make Someone Successful in This Role:
• Infrastructure and developer platform product management is a distinct craft, and this role is written for that specific kind of person
• You think in platforms and golden paths: you build once so dozens of teams can move faster, and you design for adoption rather than mandate
• You have strong opinions about what makes developer tooling great, invisible by default, indispensable once adopted, and measurable in the workflows engineers already use
• You bring enough technical depth to be a credible partner in architecture and trade-off discussions, comfortable talking through Kubernetes, CI/CD, networking, APIs, and observability with the engineers who own them
• You are fluent in where AI and agentic workflows are heading, with a healthy sense of where automation earns its place and where it does not
• You become a subject matter expert quickly, you influence without authority across a technical organization, and you balance a long-term platform vision against the near-term needs of the teams depending on you
• Above all, you measure success by what the consuming teams feel: how fast they can build and ship, how much they can do on their own, and how reliably it all runs
• Responsibilities:
• Platform and AI Dev Tools Strategy and Roadmap:
• Define and execute the long-term product strategy for Docker's internal developer platform and AI developer tooling, spanning infrastructure, self-service, CI/CD, and AI-powered and agentic workflows
• Drive an integrated roadmap that balances foundational platform investments with the AI-native capabilities that differentiate Docker
• Align platform and tooling strategy with Docker's business objectives and product portfolio, in partnership with engineering and executive leadership
• Platform as a Product and Self-Service:
• Treat the internal platform as a product: define golden paths, paved roads, and self-service capabilities that let teams provision, deploy, observe, and operate with minimal friction and strong guardrails
• Establish clear contracts, defaults, and documentation, and drive adoption through measurable outcomes rather than mandate
• Partner with infrastructure teams to translate reliability, scale, networking, and cost priorities into a roadmap teams can trust
• AI and Agentic Product Direction:
• Shape where AI agents and assisted workflows earn their place across the SDLC and operations, from code authoring and review to incident response, with a bias toward safe, auditable, human-reviewed automation
• Partner with engineering to decide what to build versus integrate across a fast-moving AI and developer infrastructure landscape
• Define how AI tooling effectiveness is measured: adoption, productivity gains, and developer satisfaction
• Productization from Internal to Customer-Facing:
• Identify which internal tools and platform capabilities are ready to become customer-facing offerings, and own the strategy that takes them from prototype to product
• Partner with product, design, and go-to-market teams to shape positioning, packaging, and the path to GA for graduated capabilities
• Bring customer and market insight back into the internal platform roadmap
• Cross-Functional Stakeholder Leadership:
• Build deep relationships with product and engineering leaders across Docker to understand their roadmaps and surface platform enablement opportunities
• Influence roadmaps by articulating platform constraints, trade-offs, and opportunities, and drive alignment when teams' needs compete
• Serve as the trusted product advisor on infrastructure and developer tooling decisions across the organization
• Measurement and Outcomes:
• Define and track the metrics that matter: platform adoption, reduction in support load and toil, provisioning and deployment speed, reliability, and developer productivity
• Use data to prioritize investment and to demonstrate the business impact of platform and AI tooling work
• What to Expect:
• First 15 Days:
• Build relationships with engineering leaders, principal and staff engineers, Security, and the product teams who depend on the platform
• Map the current landscape across both halves of the organization: infrastructure and self-service maturity, CI/CD state, the AI tooling already in production, and the biggest sources of toil and friction
• Review existing roadmaps and technical documentation to identify quick wins and longer-term opportunities
• First 45 Days:
• Publish an integrated product strategy and roadmap spanning the internal platform and AI dev tools, with clear priorities and success metrics
• Establish lightweight consultation and intake processes so teams understand platform capabilities, constraints, and how to plug in
• Deliver an early win that unblocks teams or demonstrates value from a platform or AI tooling investment, and define the instrumentation to measure adoption and impact
• One Year Outlook (First Year):
• Become the trusted product advisor for infrastructure and developer tooling across Docker, with measurable improvements in provisioning and deployment speed, self-service adoption, and reduced toil
• Lead an integrated roadmap that pairs durable platform foundations, for example self-service provisioning, multi-region networking, and paved-road delivery, with AI-native capabilities that change how Docker engineers build and operate
• Take at least one internal capability through the path to a customer-facing offering, partnering with product and go-to-market teams