Docker seeks to improve developer productivity by building AI-powered developer tools, transforming how developers write code, debug issues, deploy applications, and respond to incidents, both internally and for customers worldwide
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
- Internship or project experience with AI/ML technologies, LLM APIs, or chatbots
- Exposure to AI agent frameworks (LangChain, LangGraph, CrewAI) or similar tools
Responsibilities
- 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
Other
- Self-motivated with ability to work autonomously while knowing when to ask for help
- Passion for developer tools and user experience
- Good communication skills in remote, asynchronous environments with ability to document technical decisions
- Collaborative mindset with eagerness to learn from code reviews and feedback
- 16 weeks of paid Parental leave
