Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.
We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.
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Docker AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance—so developers can focus on building incredible AI agents, not gluing together infrastructure.
The Gateway sits at the center of modern AI applications, offering:
A model and tool routing layer with built-in security and cost optimization
A familiar OpenAI-compatible interface and MCP server
Unified observability and policy enforcement
Auto-RAG, tool injection, session summarization, and more
We’re just getting started—and we need exceptional engineers to help us build the backbone of the future of agent-based development.
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Design and implement core systems powering the AI Gateway, including the model router, MCP gateway, and control plane
Build infrastructure that supports dynamic model selection/routing, auto-failover, cost-based routing, and policy enforcement
Own critical capabilities such as secure credential storage, session summarization, caching, and rate limiting
Develop APIs for developers building with OpenAI-compatible interfaces and the Model Context Protocol
Build the underlying infrastructure to support evaluation, telemetry, replay, and backtesting for agents and LLM workflows
Lead architectural decisions and mentor engineers as the team scales
Performance tuning - caching, session summarization, and rate limiting that keep the gateway fast under real production load
Contribute to roadmap planning, technical strategy, and cross-functional alignment
Building a unified abstraction over fundamentally different model and tool providers without leaking their differences into the developer experience
Making credential and identity handling for tool access both airtight and fast
Giving developers real-time and historical visibility into what their agents are doing, with policy enforcement that can't be bypassed
Keeping latency low and reliability high as traffic scales from early adopters to production fleets
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Required Qualifications:
6+ years of backend engineering experience with production-grade systems
Deep knowledge of distributed and highly scalable systems, cloud-native infrastructure, and API design
Experience building secure, high-throughput services (e.g., gateways, proxies, load balancers, policy engines)
Fluency in Go, and/or Rust (both preferred)
Familiarity with AI/ML platforms or model serving infrastructure
A strong product mindset—you're excited about building developer-facing tools
Ownership mentality with a bias for shipping, learning, and iterating
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Bonus Qualifications:
Prior experience with OpenAI, Anthropic, or similar LLM APIs
Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI)
Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways
Understanding of OAuth2.1, secret management, and cloud IAM systems
Experience with Kubernetes, Docker, and microservices architecture
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Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software.
Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications.
Impact at scale: Your work will touch tens of thousands of developers building AI-first applications.
Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking.
Remote-first culture: Work from anywhere with a team that trusts and empowers you.
Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs.
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All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location.
United States: $160,900 – $260,700 base
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Open vacancy: This posting is for an existing open role.
AI in hiring: Docker may use AI-assisted tools during our recruiting process.
Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent.
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Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.
Flexibility that fits your life – We trust you to manage your schedule while delivering great work.
Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.
Home office support – Set up your workspace for comfort and success.
Technology stipend – Equivalent to US$100 net per month to help support your work.
Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.
Parental leave – 16 weeks of paid parental leave after six months of employment.
Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.
Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
Docker swag – Because representing the whale never gets old.
Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community.
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