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 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 help 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 execution role where you'll collaborate closely with experienced engineers, learn rapidly about AI/LLM technologies, 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 may be early in your career with AI/ML technologies, but you're eager to learn about LLMs, prompt engineering, and AI agents through hands-on work. You have solid software engineering fundamentals and experience building backend systems or APIs. You're comfortable with ambiguity, enjoy experimenting with new technologies, and learn quickly through iteration. You take ownership of your work, communicate clearly in remote environments, and actively seek feedback to improve. You think about user experience and care about building tools that developers love to use. Most importantly, you're collaborative, ask great questions, and thrive in a supportive team environment where continuous learning is encouraged.ResponsibilitiesBuild AI Developer Tool Features: Implement features for AI-powered developer tools such as code review assistants, test generators, deployment diagnostics, and on-call assistance toolsImplement LLM Integrations: Build integrations with LLM APIs (OpenAI, Anthropic, etc.) such as prompt engineering, response handling, error management, and performance optimizationContribute to Platform Infrastructure: Help build self-service platform capabilities such as deployment pipelines, observability integration, security controls, and operational tooling that enable teams to rapidly deploy AI developer toolsSupport AI-Native Development Adoption: Contribute to tools and programs that help teams adopt AI developer tools such as Claude Code, Cursor, and Warp across Docker's engineering organizationWrite Quality Code: Develop well-tested code with unit and integration tests; follow team coding standards and participate actively in code reviews to learn best practicesMaintain Production Systems: Assist with monitoring, alerting, and troubleshooting production AI systems; participate in incident response and learn operational best practicesCollaborate and Learn: Work closely with Senior Engineers and Principal Engineer on technical designs; ask questions, seek feedback, and continuously improve your skills in AI/LLM technologies and platform engineeringDocument Your Work: Create clear technical documentation for features you build; contribute to team knowledge base and help future team members understand systemsParticipate in Team Activities: Engage in design discussions, sprint planning, retrospectives, and team activities; contribute ideas for improving developer tools and team processesGrow Your Expertise: Continuously learn about AI/ML technologies, developer tooling best practices, and platform engineering patterns through hands-on work and mentorship from experienced engineersQualificationsRequired:2+ years building backend systems, APIs, or developer-facing tools with strong software engineering fundamentalsProficiency in Go (preferred), Rust, Java, or Python with understanding of data structures, algorithms, and design patternsBasic understanding of AI/ML concepts with eagerness to learn about LLM APIs, prompt engineering, and AI agent development through hands-on workExperience with cloud platforms (AWS, GCP, or Azure) and understanding of distributed systems or microservicesFamiliarity with CI/CD pipelines, automated testing, version control (Git), and modern development workflowsStrong problem-solving skills with ability to work through technical challenges with guidance from senior engineersGood communication skills in remote, asynchronous environments with ability to document technical decisionsCollaborative mindset with eagerness to learn from code reviews and feedbackSelf-motivated with ability to work autonomously while knowing when to ask for helpPassion for developer tools and user experienceBachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experiencePreferred:Internship or project experience with AI/ML technologies, LLM APIs, or chatbotsExposure to AI agent frameworks (LangChain, LangGraph, CrewAI) or similar toolsExperience with developer productivity tools, DevOps practices, or platform engineeringContributions to open source projects or personal projects involving AI toolsFamiliarity with Kubernetes, Docker, or container technologiesKnowledge of infrastructure-as-code tools (Terraform, Pulumi) or GitOps patternsUnderstanding of observability tools (Prometheus, Grafana) and monitoring best practicesComputer Science degree or equivalent technical educationWhat to ExpectFirst 30 DaysComplete onboarding and get up to speed on Docker's AI Developer Tools vision, team mission, and current Agent Dev projectMeet your team including Senior Manager, Principal Engineer, Senior Engineers, and fellow engineers; understand team dynamics and collaboration patternsLearn about Docker's developer tooling landscape including deployment systems, observability platforms, CI/CD pipelines, and existing infrastructureUnderstand Docker's LLM provider relationships, AI technology choices, and integration patterns through documentation and conversations with team membersSet up your development environment and make your first code contributions through bug fixes, documentation improvements, or small feature additionsParticipate in code reviews, design discussions, and team meetings to learn technical standards and decision-making processesBegin learning about AI/LLM technologies through self-study, pair programming with senior engineers, and hands-on experimentationFirst 90 DaysTake ownership of and deliver your first meaningful feature or component (e.g., specific AI agent capability, LLM integration module, or platform infrastructure improvement)Contribute regularly to the AI Developer Tools codebase with increasing independence and complexity of contributionsParticipate actively in code reviews both as author and reviewer; demonstrate understanding of team coding standards and best practicesEstablish monitoring and basic instrumentation for features you've shipped with support from team membersCollaborate with product and design teams to understand feature requirements and user needsBegin exploring more complex AI/LLM concepts through hands-on implementation workSupport team activities such as sprint planning, retrospectives, and design discussions with thoughtful contributionsOne Year OutlookOwn significant features or components of AI developer tools with responsibility for implementation, testing, and basic operational supportShip multiple AI agent features or platform improvements with demonstrated quality and reliabilityDevelop strong proficiency in AI/LLM integration patterns, prompt engineering, and agent development through hands-on experienceContribute meaningfully to technical discussions and design decisions with growing expertiseHelp onboard and support newer team members as you gain experienceDemonstrate measurable growth in technical skills around AI technologies, platform engineering, and developer toolsParticipate in team's success delivering developer productivity improvements and supporting productization effortsPosition yourself for growth toward Senior Engineer level through demonstrated technical excellence and increasing scope of ownershipDocker does not offer visa sponsorship for this role.We 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