Software Engineer - AI Tooling Infrastructure

About the Role
We are seeking an experienced Software Engineer to build, operate, and scale the backend infrastructure that powers innovative AI-driven developer tools. In this role, you will take ownership of production services, focusing on infrastructure that supports AI agents, developer assistants, and Model Context Protocol (MCP) integrations. You will ensure reliability, security, performance, and observability in an environment where AI-driven traffic presents unique challenges. Working closely with platform, security, and infrastructure teams, you will help design scalable architectures and improve operational excellence. This is a hands-on engineering position with significant ownership over production systems in a globally distributed, asynchronous engineering environment that values autonomy, open-source development, and continuous improvement.

Accountabilities:

• Build, deploy, operate, and scale production backend services supporting AI-powered developer tools, including MCP servers, agent skills, and AI assistants.
• Own service architecture and infrastructure decisions, enhancing system reliability, maintainability, scalability, and deployment processes.
• Define and monitor service reliability objectives (SLOs), track error budgets, and prioritize improvements in collaboration with Site Reliability Engineering (SRE) teams.
• Participate in the team's on-call rotation, investigating production incidents, coordinating resolutions, and developing incident reports, runbooks, and preventive solutions.
• Manage operational support requests and identify recurring issues that can be addressed through long-term engineering improvements.
• Design and maintain authentication and authorization systems for AI agents and machine clients, including OAuth applications, scoped tokens, permissions, and secure access management.
• Establish and maintain comprehensive observability through metrics, distributed tracing, logging, dashboards, and alerting systems.
• Manage AI agent traffic, implementing rate limits, capacity controls, cost safeguards, and mechanisms to handle dependency failures and unexpected traffic spikes.
• Collaborate with Platform, SRE, Authentication, Billing, and Edge Functions teams to enhance shared infrastructure, release processes, security, and operational practices.
• Contribute to the development of AI tooling infrastructure, with a focus on reliability, security, and performance as central engineering principles.

Requirements:

• A minimum of 5 years of experience in building, deploying, and operating production backend services, including participation in on-call rotations.
• Strong programming skills in TypeScript or Go, with practical knowledge of the other language.
• Proven track record in designing and maintaining APIs, including versioning, error handling, rate limiting, and backward compatibility.
• Strong understanding of OAuth, OpenID Connect (OIDC), JWT, and API authorization, with the capability to troubleshoot authentication and permission issues in production environments.
• Good knowledge of PostgreSQL and relational database systems.
• Experience with CI/CD pipelines, Docker, containerized deployments, and Infrastructure as Code (IaC).
• Proficiency in troubleshooting distributed systems using metrics, logs, and traces to identify performance bottlenecks and service failures.
• Excellent written and verbal communication skills, essential for collaboration across teams in a globally distributed, asynchronous environment.
• Demonstrated adaptability and ownership, with the ability to navigate ambiguity while delivering solutions in fast-paced engineering contexts.
• Deep expertise in at least one of the following areas:
  • APIs and Authentication: Experience with designing permission models, token scopes, and OAuth flows for third-party integrations or machine clients, including safely migrating authentication systems without disrupting existing users.
  • Production Operations: Hands-on experience managing production services, developing alerts and runbooks, and implementing SLOs to improve system reliability.
  • Gateways and Distributed Systems: Background in building or operating proxies, gateways, or distributed services, with skills for troubleshooting retries and handling upstream outages effectively.

Nice to Have:

• Experience with AI agent tooling, Model Context Protocol (MCP), or infrastructure supporting AI agents and LLM clients.
• Background in extracting services from larger codebases while maintaining compatibility with existing integrations.
• Familiarity with observability platforms like Grafana, OpenTelemetry, or Logflare, with practical experience in implementing SLOs.
• Contributions to open-source projects, specifically in the Node.js, Go, TypeScript, or API tooling ecosystems.

Benefits:

• Fully Remote: Work from anywhere in the world, with no office attendance requirements.
• Co-working Allowance: Access to a WeWork membership or co-working budget to support your preferred working environment.
• Equity Ownership: Participate in the Employee Stock Option Plan (ESOP) for long-term growth.
• Technology Allowance: Access a dedicated budget for professional equipment including laptops, monitors, headphones, and other essentials.
• Health Insurance: Full health insurance coverage for employees and 80% for dependents, regardless of location.
• Annual Company Off-sites: Join colleagues for a company-wide gathering in a different city each year.
• Flexible Working Arrangements: Enjoy an asynchronous work culture with the flexibility to organize your schedule and responsibilities.
• Professional Development: Annual allowance for learning and education, including courses, books, and conferences.
• Global Collaboration: Contribute to an international, remote-first engineering team spanning over 60 countries and 20 languages.