{"id":2654619,"url":"https://alion.io/job/docker-staff-software-engineer-ai-gateway","title":"Staff Software Engineer, AI Gateway","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":"2026-10-16T05:45:00Z"}},"role":"Backend","role_family":"Backend","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":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":184000,"max_usd":306000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":452},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AutoGPT","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"Go","optional":false},{"name":"IAM","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"RAG","optional":false},{"name":"Rust","optional":false}],"status":"live","first_seen_at":"2026-10-15T21:00:11Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-16T10:53:30Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"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 AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance - so developers can focus on building incredible AI agents, not gluing together infrastructure.\nThe Gateway sits at the center of modern AI applications, offering:\nA model and tool routing layer with built-in security and cost optimization\n\nA familiar OpenAI-compatible interface and MCP server\n\nUnified observability and policy enforcement\n\nAuto-RAG, tool injection, session summarization, and more\n\nWe’re just getting started and we need exceptional engineers to help us build the backbone of the future of agent-based development.\nWhat You’ll Do\nSet technical direction for core systems powering the AI Gateway 0 the model router, MCP gateway, and control plane - and make sure architectural decisions hold up as usage scales by 10x\n\nConsistently identify gaps in our infrastructure, process, or tooling before they become blockers, and drive the fix from idea to production\n\nTake a significant, hands-on role in defining, delivering, and implementing the Gateway's technical strategy, in close partnership with engineering leadership\n\nOwn the hardest, highest-ambiguity problems in the system: dynamic model selection, auto-failover, cost-based routing, and policy enforcement that has to work end-to-end\n\nAct as the go-to expert for secure credential storage, session summarization, caching, and rate limiting - the capabilities everything else depends on\n\nBuild the infrastructure that lets us, and our customers, evaluate, replay, and backtest agent and LLM behavior with confidence\n\nMentor senior and mid-level engineers, and raise the technical bar for the team through code, design review, and example\n\nPartner with product, design, and leadership to shape not just what the control plane UI does, but where the product goes next\n\nKey Problems You’ll Help Solve\nDefine the unified abstraction layer across diverse model and tool providers (OpenAI, Anthropic, Google, AWS Bedrock) that the rest of the org builds on\n\nArchitect secure, scalable identity and credential vaulting for tool and model access, trusted enough to run at enterprise scale\n\nBuild the infrastructure for real-time and historical analytics of AI agent behavior that leadership and customers both rely on\n\nGuarantee that policy enforcement and logging work end-to-end - from prompt to tool to response - with no gaps an auditor (or attacker) could find\n\nSet the bar for developer experience through intuitive APIs and first-class observability\n\nWho You Are\nRequired Qualifications\n8+ years of backend engineering experience, with a track record of owning production-grade systems at significant scale\n\nDeep specialization in distributed systems, cloud-native infrastructure, and API design - recognized by peers and cross-functional partners as a go-to expert, not just experienced\n\nExperience building secure, high-throughput services (gateways, proxies, load balancers, policy engines), and a history of making judgment calls other engineers rely on\n\nFluency in Go and/or Rust\n\nA track record of identifying systemic gaps - in architecture, process, or tooling-- and driving the fix across team boundaries, not just within your own\n\nA strong product mindset, with real experience shaping technical direction rather than only executing against it\n\nComfortable operating with wide latitude: given a problem and significant autonomy in how to solve it, including when and who to pull in\n\nBachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience\n\nBonus Qualifications\nPrior experience with OpenAI, Anthropic, or similar LLM APIs\n\nFamiliarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI)\n\nExperience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways\n\nUnderstanding of OAuth 2.1, secret management, and cloud IAM systems\n\nExperience with Kubernetes, Docker, and microservices architecture\n\nA track record of setting technical standards that other teams or engineers went on to adopt\n\nWhy Join Us?\nWork on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software.\n\nOwn mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications.\n\nImpact at scale: Your work will touch tens of thousands of developers building AI-first applications.\n\nEngineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking.\n\nRemote-first culture: Work from anywhere with a team that trusts and empowers you.\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\nDocker swag - Because representing the whale never gets old.\n\nDocker is proud to be an equal opportunity employer. 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