At Docker, we make app development easier so developers can focus on what matters. Our remote-first team spans the globe, united by a passion for innovation and great developer experiences. With over 20 million monthly users and 20 billion image pulls, Docker is the #1 tool for building, sharing, and running apps—trusted by startups and Fortune 100s alike. We’re growing fast and just getting started. Come join us for a whale of a ride!Docker seeks a Software Engineer III to join our new AI Developer Tools team building the future of AI-powered developer productivity. This is an exciting opportunity to work on cutting-edge AI agents and tools that transform how developers write code, debug issues, deploy applications, and respond to incidents—both internally at Docker and for our customers worldwide.You'll work at the intersection of AI and developer experience, contributing to production systems that leverage LLMs and AI agents to accelerate developer workflows. You'll build AI-powered tools such as code review assistants, automated test generators, deployment diagnostics agents, and on-call assistance tools. You'll also contribute to the self-service platform that enables teams across Docker to rapidly build and deploy their own AI developer tools.Your work will directly impact how Docker's engineers build and operate services powering 20 million users. As these tools mature and demonstrate value, you'll participate in transforming them into commercial offerings for Docker's customers.This is a hands-on role where you'll work with increasing independence, collaborate closely with engineers across multiple teams, and ship production features in a fast-paced, remote-first environment that values rapid iteration and continuous learning.What Would Make Someone Successful in This RoleYou're excited about AI and its potential to transform developer productivity. You have solid experience building production systems with AI agents, and you understand the nuances of prompt engineering, agent orchestration, and evaluating AI system effectiveness. You have strong software engineering fundamentals and can work independently on day-to-day tasks with general guidance on new projects. You think in terms of products and platforms, balancing technical excellence with pragmatism to ship iteratively while maintaining high quality bars. You're comfortable navigating the rapidly evolving AI/LLM landscape, experimenting with new tools and approaches, and making pragmatic technology choices. You exercise good judgment within defined processes and demonstrate emerging strategic thinking skills. You're collaborative, communicate clearly in remote environments, build effective relationships across multiple teams, and can act as a resource for teammates when they need help. You take ownership of your work from design through deployment and operations.ResponsibilitiesBuild AI-Powered Developer Tools: Design, implement, and ship production-ready AI agents and tools that accelerate developer productivity such as code review and refactoring assistants, automated test generators, local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call tasks when handling incidentsImplement LLM Integrations: Build robust, production-grade integrations with LLM APIs (OpenAI, Anthropic, etc.) such as prompt engineering, response parsing, error handling, rate limiting, cost management, and performance optimizationDevelop Agent Orchestration Systems: Create agent frameworks and orchestration systems that enable complex multi-step workflows, tool calling, context management, and agent-to-agent communicationContribute to Platform Infrastructure: Build self-service platform capabilities that enable teams across Docker to rapidly deploy and operate their own AI developer tools such as deployment pipelines, observability integration, security controls, and operational toolingDrive Adoption of AI-Native Development: Build tools and programs that accelerate adoption of AI developer tools such as Claude Code, Cursor, and Warp across Docker's engineering organizationEnsure Production Quality: Write well-tested code with strong test coverage (unit, integration, end-to-end); establish monitoring, alerting, and operational excellence for AI systemsCollaborate Cross-Functionally: Partner with Principal Engineer and Senior Engineers on architecture, work with product and design teams on features and UX, and collaborate with platform teams (Infrastructure, Security, Data) on integrations; build effective partnerships across multiple teamsAct as Technical Resource: Help teammates solve problems and share knowledge through code reviews and technical discussionsParticipate in Operations: Take part in on-call rotation for AI developer tools; respond to incidents, debug production issues, and drive continuous improvement of system reliabilityDocument and Share: Create clear technical documentation for features you build; share patterns and learnings with the teamMeasure and Iterate: Instrument AI tools to measure adoption, effectiveness, and developer productivity impact; iterate based on data and user feedback to continuously improve developer experienceQualificationsRequired:4+ years building production-grade backend systems or developer-facing tools with strong software engineering fundamentalsHands-on production experience with AI/ML technologies including practical experience with LLM APIs (OpenAI, Anthropic, etc.), prompt engineering, and AI agent developmentProficiency in Go (preferred), Rust, Java, or Python with strong software engineering fundamentalsExperience designing and building distributed systems, microservices, or platform infrastructureStrong understanding of cloud-native systems (AWS, GCP, or Azure), APIs, and data storesSolid grasp of CI/CD, automated testing, code review practices, and modern development workflowsDemonstrated ability to work independently on day-to-day work with general guidance on new projectsProduct-minded approach to building developer tools with focus on user experience and measurable outcomesExcellent communication skills in remote, asynchronous environments with ability to document technical decisions clearlyAbility to build effective working relationships across multiple teamsOwnership mentality with bias for action and iterative deliveryComfortable working autonomously across distributed teams and navigating ambiguityBachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experiencePreferred:Contributions to open source AI tools, developer tooling, or platform engineering projectsExperience with MCP (Model Context Protocol) or similar AI agent integration standardsBackground in developer productivity, DevOps, SRE, or platform engineering domainsExperience with Kubernetes, Docker, and container orchestrationKnowledge of developer tools ecosystems (IDEs, CI/CD platforms, observability tools)Experience with infrastructure-as-code (Terraform, Pulumi) and GitOps deployment patterns (ArgoCD, FluxCD)Understanding of security, compliance, and operational best practices for production AI systemsUnderstanding of software design patterns and distributed systems principlesWhat to ExpectFirst 30 DaysGet up to speed on Docker's AI Developer Tools vision, current Agent Dev project status, and existing AI tool prototypesMeet your team, Principal Engineer, Senior Manager, and key stakeholders across product engineering and platform teamsUnderstand Docker's developer tooling landscape including deployment systems, observability platforms, and CI/CD pipelinesExplore Docker's LLM provider relationships, AI technology choices, and existing integration patternsMake meaningful contributions to the AI Developer Tools codebase through features or improvementsParticipate in design discussions and code reviews to understand team technical standards and decision-making processesBegin building relationships with engineers across multiple teamsFirst 90 DaysTake ownership of and deliver significant features with measurable impact (e.g., complete AI agent capability, LLM integration improvement, or platform infrastructure component)Work with increasing independence on day-to-day tasks; demonstrate good judgment on when to ask for guidanceContribute to platform infrastructure improvements that enable faster development and deployment of AI toolsCollaborate with product and design teams on feature requirements and user experience for AI developer toolsParticipate in user research and customer calls to understand developer pain points and validate AI tool effectivenessHelp other engineers through code reviews and technical discussionsEstablish monitoring and instrumentation for AI tools you've shipped to measure adoption and effectivenessFirst Year OutlookOwn significant components of AI developer tools platform with responsibility for design, implementation, and operationsShip multiple production AI agents and tools with demonstrated adoption and measurable productivity improvementsWork largely independently on routine work; exercise good judgment within defined processesBuild strong working relationships across Docker with product, platform, and engineering teamsAct as a reliable technical resource for teammatesDemonstrate emerging strategic thinking in your approach to problems and solutionsDrive measurable improvements in developer productivity metrics such as AI tool adoption, commit frequency, PR velocity, deployment times, and CI run timesParticipate in productization efforts as internal AI tools evolve into customer-facing offeringsContinue growing your expertise in AI/ML technologies and platform engineeringWe use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 13, 2024.Please see the independent bias audit report covering our use of Covey here.PerksFreedom & flexibility; fit your work around your lifeDesignated quarterly Whaleness Days plus end of year Whaleness breakHome office setup; we want you comfortable while you work16 weeks of paid Parental leaveTechnology stipend equivalent to $100 net/monthPTO plan that encourages you to take time to do the things you enjoyTraining stipend for conferences, courses and classesEquity; we are a growing start-up and want all employees to have a share in the success of the companyDocker SwagMedical benefits, retirement and holidays vary by countryRemote-first culture, with offices in Seattle and ParisDocker 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.#LI-REMOTE