Docker - Staff Software Engineer, AI Gateway
Requirements
• 8+ years of backend engineering experience, with a track record of owning production-grade systems at significant scale • Deep 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 • Experience building secure, high-throughput services (gateways, proxies, load balancers, policy engines), and a history of making judgment calls other engineers rely on • Fluency in Go and/or Rust • A track record of identifying systemic gaps - in architecture, process, or tooling-— and driving the fix across team boundaries, not just within your own • A strong product mindset, with real experience shaping technical direction rather than only executing against it • Comfortable operating with wide latitude: given a problem and significant autonomy in how to solve it, including when and who to pull in • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience • Prior experience with OpenAI, Anthropic, or similar LLM APIs • Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI) • Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways • Understanding of OAuth 2.1, secret management, and cloud IAM systems • Experience with Kubernetes, Docker, and microservices architecture • A track record of setting technical standards that other teams or engineers went on to adopt
Responsibilities
• Set 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 • Consistently identify gaps in our infrastructure, process, or tooling before they become blockers, and drive the fix from idea to production • Take a significant, hands-on role in defining, delivering, and implementing the Gateway's technical strategy, in close partnership with engineering leadership • Own 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 • Act as the go-to expert for secure credential storage, session summarization, caching, and rate limiting - the capabilities everything else depends on • Build the infrastructure that lets us, and our customers, evaluate, replay, and backtest agent and LLM behavior with confidence • Mentor senior and mid-level engineers, and raise the technical bar for the team through code, design review, and example • Partner with product, design, and leadership to shape not just what the control plane UI does, but where the product goes next • Key Problems You’ll Help Solve • Define the unified abstraction layer across diverse model and tool providers (OpenAI, Anthropic, Google, AWS Bedrock) that the rest of the org builds on • Architect secure, scalable identity and credential vaulting for tool and model access, trusted enough to run at enterprise scale • Build the infrastructure for real-time and historical analytics of AI agent behavior that leadership and customers both rely on • Guarantee that policy enforcement and logging work end-to-end - from prompt to tool to response - with no gaps an auditor (or attacker) could find • Set the bar for developer experience through intuitive APIs and first-class observability
Benefits
• Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software. • Work on what’s next: • Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications. • Own mission-critical infrastructure: • Impact at scale: Your work will touch tens of thousands of developers building AI-first applications. • Impact at scale: • Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking. • Engineering excellence: • Remote-first culture: Work from anywhere with a team that trusts and empowers you. • Remote-first culture: • Docker considers sponsorship on a case-by-case basis based on business needs. • United States: $170,350 – $275,550 + equity • United States: • ______________________________________________________________________ • Open vacancy: This posting is for an existing open role. • Open vacancy: • AI in hiring: Docker may use AI-assisted tools during our recruiting process. • AI in hiring: • Interview 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. • Interview recordings: • Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. • Remote-first by design • Flexibility that fits your life – We trust you to manage your schedule while delivering great work. • Flexibility that fits your life • Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. • Time to recharge • Technology stipend – Equivalent to US$100 net per month to help support your work. • Technology stipend • US$100 net per month • Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. • Learning & development • Parental leave – 16 weeks of paid parental leave after six months of employment. • Parental leave • Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. • Equity for all full-time employees • Comprehensive benefits – Medical, retirement, and paid holidays vary by country. • Docker swag – Because representing the whale never gets old. • Docker swag
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