Product Manager, AI & Agent Platform
Docker
Responsibilities Own the product strategy. Define the vision, roadmap, and success metrics for Docker’s AI & Agent Platform. Make hard tradeoff decisions about what to build, what to defer, and what to cut.
Build from zero. This is a new platform. You will define the product from the ground up — writing the first specs, prototyping with engineering, validating with customers, and iterating rapidly based on what you learn.
Drive from conception through delivery. Write requirements, work with engineering to scope and prioritize, ship iteratively, and measure outcomes. You don’t hand off specs and wait — you are in the details.
Define how pieces of the agentic ecosystem fit together. Agents need secure execution, tool connectivity, model access, governance, and observability. You will define how these capabilities compose into a coherent platform — and where Docker’s boundaries are.
Think beyond developers. Agents are becoming essential for everyone who builds, deploys, and operates software. You will ensure the platform serves the full range of people who need agents to succeed — from individual developers to platform teams to enterprise operators.
Define the developer experience. Work with design and engineering to ensure that our AI products are intuitive, powerful, and meet people where they are — whether in the CLI, IDE, or CI pipeline.
Collaborate across Docker. You will work cross-functionally to ensure coherent product experiences and go-to-market alignment.
Influence technical direction. Partner with engineering leadership on architecture decisions. You don’t need to write the code, but you need to understand the technical tradeoffs and have informed opinions about them.
Represent the customer. Engage directly with developers, enterprises, and partners. Bring their voice into every product decision.
Overcome blockers. When something is in the way — a missing integration, an unclear market signal, a technical constraint — you figure out a path forward. You don’t wait for someone else to solve the problem.
Qualifications
Experience. 10+ years of product management experience, with at least 5 years on developer tools, infrastructure, or platform products.
Deep technical fluency. You can read an architecture diagram, understand container and VM runtimes, and have a working knowledge of how AI agents, LLMs, and protocol-level tool connectivity work. You don’t need to be a hypervisor engineer, but you need to hold your own with one.
Proven ability to ship 0-to-1 products. You have taken a product from idea through launch in a fast-moving environment. You know how to operate when there is no playbook.
Builder mentality. You prototype, you sketch architectures, you test early ideas with customers before the spec is done. You are a doer, not just a thinker.
Strong product sense and UX instincts. You care about the developer experience at a deep level — from API design to CLI ergonomics to error messages.
Strategic thinking with execution follow-through. You can set a multi-year vision and also write the spec for what ships next sprint.
Comfort with ambiguity. This space is new and moving fast. You thrive when the answer isn’t obvious and you have to go find it.
Excellent communication. You can write a crisp product brief, present to executives, and debate technical tradeoffs with engineers — all in the same day.
Experience growing and monetizing products at scale. You have been part of taking a product from early adoption to meaningful revenue, and you understand the pricing, packaging, and go-to-market decisions that make that happen.
Bonus Points
Experience building products in the containers, cloud-native, or DevOps space
Experience with AI/ML developer tooling or the agentic AI ecosystem
Contributions to open source projects
Experience building and scaling a business from zero to significant ARR
What You’ll Work With
Own the product strategy. Define the vision, roadmap, and success metrics for Docker’s AI & Agent Platform. Make hard tradeoff decisions about what to build, what to defer, and what to cut.
Build from zero. This is a new platform. You will define the product from the ground up — writing the first specs, prototyping with engineering, validating with customers, and iterating rapidly based on what you learn.
Drive from conception through delivery. Write requirements, work with engineering to scope and prioritize, ship iteratively, and measure outcomes. You don’t hand off specs and wait — you are in the details.
Define how pieces of the agentic ecosystem fit together. Agents need secure execution, tool connectivity, model access, governance, and observability. You will define how these capabilities compose into a coherent platform — and where Docker’s boundaries are.
Think beyond developers. Agents are becoming essential for everyone who builds, deploys, and operates software. You will ensure the platform serves the full range of people who need agents to succeed — from individual developers to platform teams to enterprise operators.
Define the developer experience. Work with design and engineering to ensure that our AI products are intuitive, powerful, and meet people where they are — whether in the CLI, IDE, or CI pipeline.
Collaborate across Docker. You will work cross-functionally to ensure coherent product experiences and go-to-market alignment.
Influence technical direction. Partner with engineering leadership on architecture decisions. You don’t need to write the code, but you need to understand the technical tradeoffs and have informed opinions about them.
Represent the customer. Engage directly with developers, enterprises, and partners. Bring their voice into every product decision.
Overcome blockers. When something is in the way — a missing integration, an unclear market signal, a technical constraint — you figure out a path forward. You don’t wait for someone else to solve the problem.
Experience. 10+ years of product management experience, with at least 5 years on developer tools, infrastructure, or platform products.
Deep technical fluency. You can read an architecture diagram, understand container and VM runtimes, and have a working knowledge of how AI agents, LLMs, and protocol-level tool connectivity work. You don’t need to be a hypervisor engineer, but you need to hold your own with one.
Proven ability to ship 0-to-1 products. You have taken a product from idea through launch in a fast-moving environment. You know how to operate when there is no playbook.
Builder mentality. You prototype, you sketch architectures, you test early ideas with customers before the spec is done. You are a doer, not just a thinker.
Strong product sense and UX instincts. You care about the developer experience at a deep level — from API design to CLI ergonomics to error messages.
Strategic thinking with execution follow-through. You can set a multi-year vision and also write the spec for what ships next sprint.
Comfort with ambiguity. This space is new and moving fast. You thrive when the answer isn’t obvious and you have to go find it.
Excellent communication. You can write a crisp product brief, present to executives, and debate technical tradeoffs with engineers — all in the same day.
Experience growing and monetizing products at scale. You have been part of taking a product from early adoption to meaningful revenue, and you understand the pricing, packaging, and go-to-market decisions that make that happen.
Experience building products in the containers, cloud-native, or DevOps space
Experience with AI/ML developer tooling or the agentic AI ecosystem
Contributions to open source projects
Experience building and scaling a business from zero to significant ARR
We are building a new platform for agentic development. Docker Sandboxes — isolated execution environments for AI coding agents — is one of the first products in this platform and one of the fastest-growing new products in Docker’s history. But this is just the beginning. The platform will grow to span multiple product areas as we define how agents and people work together at scale.
The technologies you will work across include:
Secure, isolated execution environments (microVMs, containers, sandboxing)
Agent-to-tool connectivity and protocol standards (MCP and beyond)
AI model serving and inference infrastructure
Governance, policy enforcement, and audit controls for enterprise AI adoption
Local-to-cloud execution and workload portability
Developer CLIs, SDKs, and platform APIs
Container runtimes, image registries, and build systems
Docker does not offer visa sponsorship for this role.
Perks
Freedom & flexibility; fit your work around your life
Designated quarterly Whaleness Days plus end of year Whaleness break
Home office setup; we want you comfortable while you work
16 weeks of paid Parental leave (after 6 months of employment)
Technology stipend equivalent to $100 USD net/month
PTO plan that encourages you to take time to do the things you enjoy
Training stipend for conferences, courses and classes
Equity; we are a growing start-up and want all employees to have a share in the success of the company
Docker Swag
Medical benefits, retirement and holidays vary by country
Remote-first culture, with offices in Seattle and Paris
Docker embraces diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our company will be.
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