{"id":2542681,"url":"https://alion.io/job/docker-staff-software-engineer-ai-developer-tools","title":"Staff Software Engineer, AI Developer Tools","company":{"id":569,"name":"Docker","domain":"docker.com","url":"https://alion.io/company/docker","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":78,"open_postings":8,"ghost_share":0,"stale_share":0.875,"repost_share":0,"time_to_fill_p50_days":58,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["San Francisco, United States","Seattle, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":170350,"max":275550,"currency":"USD","period":"year","gross":null,"usd_annual":275550},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"GitOps","optional":false},{"name":"Go","optional":false},{"name":"Grafana","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Outlook","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-14T14:12:21Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T16:54:18Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About Docker\nDocker 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. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.\nWe are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.\n_______________________________________________________________________\nDocker is looking for a Staff Software Engineer to set the technical direction for key parts of our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building the AI-powered tools and the platform that let teams across Docker prototype, deploy, and scale their own AI developer tools.\nAs a Staff Engineer you will own the technical design and delivery for two areas:\nAI-Powered Developer Tools. Design and build AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents.\nSelf-Service AI Developer Tools Platform. Design and build the platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools. You will set the patterns and standards that let teams experiment, iterate quickly, and graduate successful prototypes into production-ready services.\nYou will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal engineers, engineering leadership, product engineering teams, and platform teams across Docker.\nWhat Would Make Someone Successful in This Role\nYou are a hands-on technical leader who works well at the intersection of AI, developer experience, and platform engineering. You have shipped production systems built on LLMs and AI agents, and you can explain what worked and what did not. You think in platforms: you design something once so that several teams can move faster. You have clear opinions about what makes a developer tool good, and sound judgment about when to build, when to integrate, and when not to do either. You are comfortable in a fast-moving AI landscape and balance technical quality with shipping iteratively. Before you design, you ask about scale, users, and constraints rather than assuming them. You lead through influence and mentorship, and the engineers around you get better because you are on the team.\nResponsibilities\nTechnical Leadership and Architecture\nSet technical direction and own the architecture for AI-powered developer tools and the self-service platform within the team's roadmap\n\nTurn ambiguous problems into clear requirements, plans, and staged decisions. Ask about scale, users, and constraints before designing, and write down your assumptions\n\nEstablish patterns, standards, and best practices for LLM integration, agent development, and production AI systems that the team and partner teams adopt\n\nShape platform capabilities including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, and operational tooling for AI developer tools\n\nDesign reliable, scalable infrastructure for hosting AI agents and developer tools\n\nRecommend AI technology choices, LLM provider strategies, and agent orchestration approaches, and make the trade-offs explicit\n\nWork with the Senior Manager and the team's Principal engineers to align technical decisions with business goals\n\nSystems Design and Implementation\nDesign, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation\n\nBuild self-service platform capabilities that reduce time-to-production for new AI tools from weeks to days\n\nBuild systems that speed up adoption of AI-native development tools (Claude Code, Codex) across Docker's engineering organization\n\nSet and meet reliability, security, and performance standards for AI systems, including SLOs, monitoring, incident response, and cost management\n\nDesign integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems\n\nTake part in the team's on-call rotation and use what you learn to improve alerts, runbooks, and tooling\n\nStrategic Impact and Innovation\nEvaluate emerging AI/LLM technologies, developer tooling trends, and agent frameworks, and recommend what Docker should adopt and what it should not build\n\nDefine how we measure AI tool effectiveness, including adoption, productivity gains, and developer satisfaction\n\nImprove AI tool performance, cost efficiency, and developer experience through architectural improvements\n\nContribute to the technical approach for hardening proven internal tools so other teams across Docker can adopt them\n\nLead cross-team technical delivery, surface risks early, and work with Infrastructure, Security, and Data on shared standards\n\nLeadership and Mentorship\nMentor senior engineers on AI/LLM integration patterns, agent development, and platform engineering practices\n\nLead design reviews and raise the quality of design and code reviews across the team\n\nCreate reusable patterns, documentation, and architectural decision records (ADRs) that other engineers build on\n\nHelp the team turn good individual AI-assisted engineering practice into shared workflows and controls\n\nThis role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed.\n\nQualifications\nRequired\n8+ years of software engineering experience, with demonstrated technical leadership on production systems at scale\n\nHands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools\n\nStrong understanding of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows\n\nTrack record of designing and building scalable distributed systems and developer-facing platforms\n\nProduction experience with cloud-native infrastructure, including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines\n\nProficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals\n\nExperience designing developer tools, platform systems, or internal tools that other teams rely on\n\nTrack record of clarifying requirements and constraints with stakeholders before committing to a design\n\nTrack record of leading complex initiatives that crossed team boundaries, and of influencing without direct authority\n\nStrong product and platform judgment: you weigh business outcomes, developer experience, and technical trade-offs\n\nClear written and spoken communication suited to a remote, async-first company\n\nTrack record of mentoring other experienced engineers\n\nOwnership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments\n\nBachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience\n\nPreferred\nExperience with MCP (Model Context Protocol) or similar AI agent integration standards\n\nBackground in developer productivity, DevOps, SRE, or platform engineering\n\nContributions to open source AI tools, developer tooling, or platform engineering projects\n\nExperience evolving an internal platform or tool into a widely adopted, production-grade service\n\nKnowledge of security, compliance, and operational practices for production AI systems\n\nExperience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure)\n\nWhat to Expect\nFirst 30 Days\nBuild context on Docker's current AI and developer tooling landscape, including existing AI experiments, LLM provider relationships, and architecture decisions to date\n\nMeet the Senior Manager, the team's Principal engineers, engineering leadership, and key stakeholders in product engineering to understand needs, pain points, and constraints\n\nReview existing AI tool prototypes and internal experiments to learn what is working and what is not\n\nGet hands-on with the team's services and ship a useful production change\n\nShadow on-call and learn the operational profile of the team's services\n\nWork with the Senior Manager to agree on initial technical priorities\n\nFirst 90 Days\nLead the technical framing and delivery plan for one significant problem, from requirements through to production\n\nDocument the architecture, technology choices, and integration patterns for that work, including ADRs\n\nShip a production AI developer tool that sets patterns the team can reuse (for example an AI-powered code review agent, a deployment diagnostic agent, or an on-call assistant)\n\nContribute to the technical foundations of the self-service platform: deployment pipeline, observability integration, security controls, and cost management\n\nLead design reviews for your area of the roadmap and begin mentoring other engineers\n\nTake part in the on-call rotation\n\nFirst Year Outlook\nBe the trusted technical lead for your area of AI Developer Tools, and a sought-after partner for teams across Docker\n\nDeliver at least one material outcome that spans multiple teams or systems\n\nHave multiple production AI tools demonstrating value across Docker's engineering organization\n\nHelp build a self-service platform that lets multiple teams build, deploy, and operate their own AI tools with little friction\n\nDefine and instrument how the team measures AI tool adoption, effectiveness, and developer productivity impact\n\nGrow other senior engineers into broader ownership, and reduce the number of decisions that depend on a small set of people\n\nDocker considers sponsorship on a case-by-case basis based on business needs.\nCompensation & Equity\nUnited States: $170,350 - $275,550 + equity\n______________________________________________________________________\nPosting Information\nOpen vacancy: This posting is for an existing open role.\n\nAI in hiring: Docker may use AI-assisted tools during our recruiting process.\n\nInterview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent.\n\n______________________________________________________________________\nPerks & Benefits\nRemote-first by design - Work from your home, with offices in Seattle and Paris for connection and collaboration.\n\nFlexibility that fits your life - We trust you to manage your schedule while delivering great work.\n\nTime to recharge - Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.\n\nHome office support - Set up your workspace for comfort and success.\n\nTechnology stipend - Equivalent to US$100 net per month to help support your work.\n\nLearning & development - Annual stipend for conferences, courses, certifications, and continued learning.\n\nParental leave - 16 weeks of paid parental leave after six months of employment.\n\nEquity for all full-time employees - Share in Docker's long-term success as we continue to grow.\n\nComprehensive benefits - Medical, retirement, and paid holidays vary by country.\n\nDock...","description_format":"text","description_chars":12331,"description_truncated":true,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Home office","Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"San Francisco","iso":null,"kind":"city"},{"name":"Seattle","iso":null,"kind":"city"}],"hiring_excludes":[],"relocation_offered":false,"industries":["DevOps & Platform Engineering","Virtualization & Containers","Developer Tools"],"lifecycle":[{"event":"open","at":"2026-10-14T15:59:59Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":0,"expected_fill_days":58,"reasons":["conf:3","velocity","win:early"],"computed_at":"2026-10-15T05:46:00Z"},"pay":{"stated_usd_annual":275550,"is_top_pay":false},"html_url":"https://alion.io/job/docker-staff-software-engineer-ai-developer-tools","json_url":"https://alion.io/job/docker-staff-software-engineer-ai-developer-tools.json","meta":{"generated_at":"2026-10-15T18:48:42Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":28458,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-16T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":569},"rest":"https://alion.io/mcp/rest/get_company?id=569"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fdocker-staff-software-engineer-ai-developer-tools"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fdocker-staff-software-engineer-ai-developer-tools"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fdocker-staff-software-engineer-ai-developer-tools"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/docker-staff-software-engineer-ai-developer-tools\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fdocker-staff-software-engineer-ai-developer-tools"}]}