Docker
Senior Software Engineer, AI Developer Tools
$161K–$261K
San Francisco, CA +1 · Remote · Senior · Full-time · Posted Oct 14, 2026
- Location
- San Francisco, CA
Seattle, WA - Experience
- 6+ years of software engineering experience building and operating production systems.
- Education
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Visa sponsorship
- Docker considers visa sponsorship on a case-by-case basis based on business needs.
About the job
Build and operate AI-powered developer tools and a self-service platform that helps Docker teams prototype, deploy, and scale their own AI tools.
What you'll do
- Design and operate production AI agents for developer productivity, including code review, test generation, deployment diagnostics, and incident response.
- Build platform capabilities and integrations with CI/CD, observability, and deployment systems so teams can ship AI tools faster.
- Own features from requirements through production, including design documentation, code review, reliability, and on-call support.
What they ask for
- 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, prompt engineering, and agent orchestration.
- Experience with scalable backend services, distributed systems, or developer-facing platforms, and cloud-native infrastructure including Kubernetes, CI/CD, and observability.
- Proficiency in Go (preferred), Rust, Java, or Python; bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Nice to have
- Experience with MCP or similar AI agent integration standards.
- Background in developer productivity, DevOps, SRE, or platform engineering.
Pay
$160,900 – $260,700 USD base salary
Tools
OpenAI, Anthropic, Kubernetes, ArgoCD, Grafana, Go, Rust, Python
AI focus
Build production AI agents and developer tools, integrate LLM providers and agent frameworks, and develop platform infrastructure for teams to deploy AI tools.
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