Familiarity with containerized environments (Docker, Kubernetes)
Strong software engineering fundamentals: testing, CI/CD, version control, design reviews
Bonus (High Impact)
Experience building developer tools or infrastructure platforms
Experience in ML infrastructure, model serving, or AI tooling
Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry)
Experience with WebSockets or streaming architectures
Performance optimization at scale
Experience building internal platforms used by engineers
Responsibilities
You will own end-to-end product surfaces across our developer platform:
Design and implement high-performance web applications for AI infrastructure tooling
Build scalable backend systems that interact with distributed inference and training services
Architect APIs and service layers that serve enterprise and research customers
Develop observability dashboards, experiment tracking UIs, and performance analytics tools
Optimize real-time streaming interfaces for model inference workflows
Work closely with ML engineers and infra teams to expose complex systems through intuitive product surfaces
Lead architectural decisions for frontend-backend communication, state management, and performance tuning
Ship production-grade features in fast iteration cycles
You will not just “write UI.”
You will build the control plane for frontier AI systems. Your work will directly power:
Large-scale LLM inference systems
Reinforcement learning training platforms
Evaluation and experimentation frameworks
Developer-facing AI infrastructure products
This is not CRUD dashboard engineering. This is building the operating system for AI builders. ### Compensation
We offer competitive compensation with equity, comprehensive health benefits, and flexible work arrangements. Compensation is determined by location, level, and experience.
