About the Role
Job Description:
• Build AI Developer Tool Features: Implement features for AI-powered developer tools such as code review assistants, test generators, deployment diagnostics, and on-call assistance tools
• Implement LLM Integrations: Build integrations with LLM APIs (OpenAI, Anthropic, etc.) such as prompt engineering, response handling, error management, and performance optimization
• Contribute 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 tools
• Support 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 organization
• Write Quality Code: Develop well-tested code with unit and integration tests; follow team coding standards and participate actively in code reviews to learn best practices
• Maintain Production Systems: Assist with monitoring, alerting, and troubleshooting production AI systems; participate in incident response and learn operational best practices
• Collaborate 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 engineering
• Document Your Work: Create clear technical documentation for features you build; contribute to team knowledge base and help future team members understand systems
• Participate in Team Activities: Engage in design discussions, sprint planning, retrospectives, and team activities; contribute ideas for improving developer tools and team processes
• Grow Your Expertise: Continuously learn about AI/ML technologies, developer tooling best practices, and platform engineering patterns through hands-on work and mentorship from experienced engineers
Requirements:
• 2+ years building backend systems, APIs, or developer-facing tools with strong software engineering fundamentals
• Proficiency in Go (preferred), Rust, Java, or Python with understanding of data structures, algorithms, and design patterns
• Basic understanding of AI/ML concepts with eagerness to learn about LLM APIs, prompt engineering, and AI agent development through hands-on work
• Experience with cloud platforms (AWS, GCP, or Azure) and understanding of distributed systems or microservices
• Familiarity with CI/CD pipelines, automated testing, version control (Git), and modern development workflows
• Strong problem-solving skills with ability to work through technical challenges with guidance from senior engineers
• Good communication skills in remote, asynchronous environments with ability to document technical decisions
• Collaborative mindset with eagerness to learn from code reviews and feedback
• Self-motivated with ability to work autonomously while knowing when to ask for help
• Passion for developer tools and user experience
Benefits:
• 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
• Technology stipend equivalent to $100 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
Docker most often refers to:A dockworker, a manual laborer who is involved in loading and unloading ships, also called a longshoreman or stevedore
Docker (software), an open-source software project automating the deployment of applications inside software containers
Docker, Inc., the company promoting Docker software
