Staff Software Engineer, AI Developer Tools

About Docker:

Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. Developers rely on Docker to build, share, and run their applications across Docker Desktop, Docker Hub, and Docker Scout.

Docker is a globally distributed, remote-first team building the tools that define how software gets built and delivered.

Role Overview:

Docker is looking for a Staff Software Engineer to set the technical direction for key parts of the AI Developer Tools team. You will own the technical design and delivery for two areas:

• AI-Powered Developer Tools: Design and build AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews, including code review assistants, test generators, deployment diagnostic agents, and on-call incident assistants.
• Self-Service AI Developer Tools Platform: Design and build platform infrastructure that lets product and platform teams prototype, build, and deploy their own AI developer tools, and graduate successful prototypes into production-ready services.

You will report to the Senior Manager, AI Developer Tools, and work closely with Principal engineers, engineering leadership, product engineering, and platform teams.

Responsibilities:

• Set technical direction and own architecture for AI-powered developer tools and the self-service platform.
• Turn ambiguous problems into clear requirements, plans, and staged decisions.
• Establish patterns and standards for LLM integration, agent development, and production AI systems.
• Shape platform capabilities including deployment frameworks (ArgoCD/GitOps), observability (Grafana), security controls, and operational tooling.
• Design reliable, scalable infrastructure for hosting AI agents and developer tools.
• Recommend AI technology choices, LLM provider strategies, and agent orchestration approaches, making trade-offs explicit.
• Design, build, and operate production AI agents for developer productivity.
• Build self-service platform capabilities that reduce time-to-production for new AI tools from weeks to days.
• Set and meet reliability, security, and performance standards, including SLOs, monitoring, incident response, and cost management.
• Design integrations with CI/CD pipelines, observability platforms, and deployment systems.
• Take part in the team's on-call rotation.
• Evaluate emerging AI/LLM technologies and agent frameworks.
• Define how to measure AI tool effectiveness, including adoption, productivity gains, and developer satisfaction.
• Lead cross-team technical delivery and work with Infrastructure, Security, and Data on shared standards.
• Mentor senior engineers and lead design and code reviews.
• Create reusable patterns, documentation, and architectural decision records (ADRs).
• May require on-call participation outside standard business hours, as needed.

Required Qualifications:

• 8+ years of software engineering experience, with demonstrated technical leadership on production systems at scale.
• Hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools.
• Strong understanding of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, and agent orchestration frameworks.
• Track record of designing scalable distributed systems and developer-facing platforms.
• Production experience with cloud-native infrastructure, including Kubernetes, GitOps, observability systems, and CI/CD pipelines.
• Proficiency in Go (preferred), Rust, Java, or Python.
• Experience designing developer tools, platform systems, or internal tools that other teams rely on.
• Track record of clarifying requirements with stakeholders, leading cross-team initiatives, and mentoring experienced engineers.
• Strong product and platform judgment.
• Clear written and spoken communication suited to a remote, async-first company.
• Ownership mentality with a bias for action and iterative delivery.
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Preferred Qualifications:

• 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 evolving an internal platform into a widely adopted, production-grade service.
• Knowledge of security, compliance, and operational practices for production AI systems.
• Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure).

Compensation and Equity:

United States: $170,350 – $275,550 + equity.

Perks and Benefits:

• Remote-first by design, with offices in Seattle and Paris.
• Flexible scheduling.
• Generous PTO, quarterly Whaleness Days, and an end-of-year Whaleness break.
• Home office support.
• Technology stipend of US$100 net per month.
• Annual learning and development stipend.
• 16 weeks of paid parental leave after six months of employment.
• Equity for all full-time employees.
• Comprehensive benefits, including medical, retirement, and paid holidays, which vary by country.
• Docker swag.

Docker is an equal opportunity employer.