Senior Software Engineer, AI Gateway
Docker is hiring a Senior Software Engineer, AI Gateway for a remote role open to applicants in United States. It pays $161k-$261k a year and Level rates it ; you can apply on Level.
AI in this role
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. 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.
We 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.
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Docker 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.
The Gateway sits at the center of modern AI applications, offering:
A model and tool routing layer with built-in security and cost optimization
A familiar OpenAI-compatible interface and MCP server
Unified observability and policy enforcement
Auto-RAG, tool injection, session summarization, and more
We’re just getting started—and we need exceptional engineers to help us build the backbone of the future of agent-based development.
What You’ll Do
Design and implement core systems powering the AI Gateway, including the model router, MCP gateway, and control plane
Build infrastructure that supports dynamic model selection/routing, auto-failover, cost-based routing, and policy enforcement
Own critical capabilities such as secure credential storage, session summarization, caching, and rate limiting
Develop APIs for developers building with OpenAI-compatible interfaces and the Model Context Protocol
Build the underlying infrastructure to support evaluation, telemetry, replay, and backtesting for agents and LLM workflows
Lead architectural decisions and mentor engineers as the team scales
Performance tuning - caching, session summarization, and rate limiting that keep the gateway fast under real production load
Contribute to roadmap planning, technical strategy, and cross-functional alignment
Key Problems You’ll Help Solve
Building a unified abstraction over fundamentally different model and tool providers without leaking their differences into the developer experience
Making credential and identity handling for tool access both airtight and fast
Giving developers real-time and historical visibility into what their agents are doing, with policy enforcement that can't be bypassed
Keeping latency low and reliability high as traffic scales from early adopters to production fleets
Who You Are
Required Qualifications:
6+ years of backend engineering experience with production-grade systems
Deep knowledge of distributed and highly scalable systems, cloud-native infrastructure, and API design
Experience building secure, high-throughput services (e.g., gateways, proxies, load balancers, policy engines)
Fluency in Go, and/or Rust (both preferred)
Familiarity with AI/ML platforms or model serving infrastructure
A strong product mindset—you're excited about building developer-facing tools
Ownership mentality with a bias for shipping, learning, and iterating
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Bonus Qualifications:
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 OAuth2.1, secret management, and cloud IAM systems
Experience with Kubernetes, Docker, and microservices architecture
Why Join Us?
Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software.
Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications.
Impact at scale: Your work will touch tens of thousands of developers building AI-first applications.
Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking.
Remote-first culture: Work from anywhere with a team that trusts and empowers you.
Docker considers visa sponsorship on a case-by-case basis based on business needs.
Compensation & Equity
United States: $160,900 – $260,700 + equity
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Posting Information
Open vacancy: This posting is for an existing open role.
AI in hiring: Docker may use AI-assisted tools during our recruiting process.
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.
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Perks & Benefits
Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.
Flexibility that fits your life – We trust you to manage your schedule while delivering great work.
Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.
Home office support – Set up your workspace for comfort and success.
Technology stipend – Equivalent to US$100 net per month to help support your work.
Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.
Parental leave – 16 weeks of paid parental leave after six months of employment.
Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.
Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
Docker swag – Because representing the whale never gets old.
Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community.
#LI-REMOTE
How we rate this
Senior Software Engineer, AI Gateway at Docker rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $161k
- Typical software engineer job
- $168k
This posting starts close to the typical software engineer job. See software engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What are the limits of OpenAI that you've run into, and how did you work around them?
- What's a project where you used Anthropic hands-on?
- Walk me through how you've used LangChain in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, OpenAI, Anthropic, and LangChain. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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