Staff Software Engineer, AI Developer Tools

Docker, Inc

. Set technical direction and own architecture for AI-powered developer tools and the self-service AI developer tools platform .

Posted 10/14/2026full-timeRemote • United StatesLead💰 $170,350 - $275,550 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building AI-powered developer tools, with a strong focus on LLM integration, scalable infrastructure, and cross-team collaboration. Proficient in leading technical delivery, mentoring engineers, and establishing operational standards for production AI systems.

Highest-signal resume keywords

AI-Powered Developer ToolsLLM IntegrationKubernetesGo ProgrammingCross-Team Technical Delivery

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringLLM APIsPrompt EngineeringAgent Orchestration FrameworkScalable Distributed SystemsCI/CD PipelinesGitOps Deployment PatternsDeveloper Tools DesignProduction AI SystemsObservability Systems

Soft Skills

Clear CommunicationMentoringOwnership MentalityInfluencing Without AuthorityIterative Delivery

Tools & Technologies

TerraformPulumiAWSGCPAzure

Certifications & Qualifications

Bachelor's Degree in Computer ScienceEngineering Degree

Industry Keywords

DevOpsSREPlatform EngineeringDeveloper ProductivitySecurity Practices

Tech Stack

Tools & technologies

AWSAzureDistributed SystemsDockerGoogle Cloud PlatformJavaKubernetesOpen SourcePythonRustTerraformGo

About the role

Key responsibilities & impact

Set technical direction and own architecture for AI-powered developer tools and the self-service AI developer tools platform
Turn ambiguous problems into requirements, plans, and staged decisions
Establish patterns and standards for LLM integration, agent development, and production AI systems
Shape deployment, observability, security, and operational capabilities for AI developer tools
Design reliable, scalable infrastructure for hosting AI agents and developer tools
Recommend AI technology, LLM provider, and agent orchestration strategies
Design, build, and operate production AI agents for code review, test generation, deployment diagnostics, and incident response
Build self-service platform capabilities that reduce time-to-production for new AI tools
Accelerate adoption of Claude Code and Codex across Docker engineering
Set reliability, security, performance, monitoring, incident response, SLO, and cost-management standards
Integrate AI developer tools with CI/CD, observability, and deployment systems
Participate in on-call rotation and improve alerts, runbooks, and tooling
Evaluate emerging AI/LLM technologies, developer tooling trends, and agent frameworks
Define measures of AI tool adoption, productivity gains, and developer satisfaction
Lead cross-team technical delivery with Infrastructure, Security, and Data
Mentor senior engineers and lead design and code reviews
Create reusable patterns, documentation, and architectural decision records
Help establish shared AI-assisted engineering workflows and controls

Requirements

What you’ll need

8+ years of software engineering experience
Hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools
Strong understanding of LLM APIs including OpenAI and Anthropic
Prompt engineering experience
Agent orchestration framework experience
Experience designing scalable distributed systems and developer-facing platforms
Production experience with Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines
Proficiency in Go, Rust, Java, or Python; Go preferred
Experience designing developer tools, platform systems, or internal tools
Experience clarifying requirements and constraints with stakeholders
Experience leading cross-team initiatives and influencing without direct authority
Strong product and platform judgment
Clear written and spoken communication suited to a remote, async-first company
Experience mentoring experienced engineers
Ownership mentality and iterative delivery in ambiguous environments
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Experience with MCP or similar AI agent integration standards preferred
Background in developer productivity, DevOps, SRE, or platform engineering preferred
Contributions to open source AI tools, developer tooling, or platform engineering projects preferred
Experience evolving an internal platform into a widely adopted production-grade service preferred
Knowledge of security, compliance, and operational practices for production AI systems preferred
Experience with Terraform, Pulumi, AWS, GCP, or Azure preferred
Ability to work in the United States
May require participation in an on-call rotation outside standard business hours

Benefits

Comp & perks

Equity for all full-time employees
Remote-first work from home
Flexible scheduling
Generous PTO
Quarterly Whaleness Days
End-of-year Whaleness break
Home office support
Technology stipend equivalent to US$100 net per month
Annual learning and development stipend for conferences, courses, certifications, and continued learning
16 weeks of paid parental leave after six months of employment
Medical benefits
Retirement benefits
Paid holidays
Docker swag