Senior Software Engineer, AI Gateway

About [Employer]

[Employer] 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 [Employer] to build, share, and run their applications across our suite of products including [Employer] Desktop, [Employer] Hub, and [Employer] 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, [Employer] 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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The Role

[Employer] 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.

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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
• Take part in on-call rotation for your team, respond to incidents, debug production issues, and drive continuous improvement of system reliability

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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, [Employer], and microservices architecture

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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.

Visa sponsorship: [Employer] considers visa sponsorship on a case-by-case basis based on business needs.

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Compensation & Equity

All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location.

United States: $160,900 – $260,700 base

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Posting Information

• Open vacancy: This posting is for an existing open role.
• AI in hiring: [Employer] 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 [Employer]'s long-term success as we continue to grow.
• Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
• [Employer] swag – Because representing the whale never gets old.

[Employer] 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.

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