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Salary: USD 160,900 - 260,700 / annual
Docker is hiring a Senior Software Engineer to build AI-powered developer tools and the platform infrastructure that enables teams across the company to prototype, deploy, and scale their own AI developer tools.
You will work at the intersection of AI, developer experience, and platform engineering. The role involves designing, building, and operating production AI agents that accelerate developer productivity—including code review assistants, test generators, deployment diagnostics, and incident response automation. You'll integrate LLM providers, agent orchestration frameworks, and MCP servers into reliable tools following team patterns and standards. You'll also build and improve platform capabilities including deployment pipelines (ArgoCD/GitOps), observability integration (Grafana), security controls, and cost management to help teams ship AI tools faster.
Key responsibilities include: designing and operating production AI agents for developer productivity; integrating LLM providers and agent frameworks into reliable systems; building platform capabilities that reduce time-to-production from weeks to days; taking features from requirements to production with clear design documents; participating in code reviews and design reviews; contributing to reliability, security, and performance standards for AI systems; and helping newer engineers learn the team's tools and practices. You'll also participate in the team's on-call rotation and help improve operational tooling.
You'll report to the Senior Manager of AI Developer Tools and work closely with Principal and Staff engineers, product engineering teams, and platform teams across Docker. Docker is a globally distributed, remote-first team with offices in Seattle and Paris. The company has 20+ million monthly users and 20+ billion container image pulls, and is positioned at the center of how AI agents are redefining software development.
REQUIREMENTS
Required:
- 6+ years of software engineering experience building and operating production systems
- Hands-on experience building LLM-powered applications, AI agents, or AI-assisted developer tools
- Working knowledge of LLM APIs (OpenAI, Anthropic, others), prompt engineering, agent orchestration frameworks, and practical AI use in software development workflows
- Experience building and operating scalable backend services, distributed systems, or developer-facing platforms
- Experience with cloud-native infrastructure including Kubernetes, CI/CD pipelines, and observability systems
- Proficiency in Go (preferred), Rust, Java, or Python with strong software engineering fundamentals
- Experience building developer tools, platform systems, or internal tools that other engineers rely on
- Good product judgment: ability to weigh developer experience and technical trade-offs, ask clarifying questions before committing to design
- Clear written and spoken communication suited to remote, async-first company
- Ownership mentality with bias for action and iterative delivery in ambiguous, fast-moving environments
- Comfortable working autonomously in distributed, remote-first team
- Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience
Preferred:
- Experience with MCP (Model Context Protocol) or similar AI agent integration standards
- Background in developer productivity, DevOps, SRE, or platform engineering
- Contributions to open source AI tools, developer tooling, or platform engineering projects
- Experience with GitOps deployment patterns (ArgoCD) or Grafana-based observability
- Familiarity with security and operational practices for production AI systems
- Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure)
