About the company
Our client is a software company.
The role
Raydar is recruiting for this role on behalf of our client. Own the internal infrastructure and developer tooling that helps engineering and research colleagues build, ship and run software with confidence. This is a hands-on, high-ownership position that blends infrastructure work, automation and machine learning operations.
What you'll do
- Design, build and maintain core infrastructure for research and production environments, including cloud compute, storage, CI/CD, observability and security.
- Develop internal developer tools, automation and shared libraries that raise productivity across teams.
- Create dependable pipelines and services that take models from early experiments through testing and into live use.
- Define and improve build, test and release workflows so work moves smoothly from prototype to production.
- Set up monitoring for system health and performance across services and pipelines.
- Work with research and product colleagues to find bottlenecks, streamline workflows and keep results repeatable.
- Contribute to infrastructure strategy and architecture as the organization grows.
Requirements
What we're looking for
- Strong technical fundamentals, including concurrency and software architecture, and comfort working with AI-assisted engineering.
- Solid backend engineering experience with Python or Go, APIs, databases and distributed systems.
- Working depth in Kubernetes and a major cloud provider.
- Practical production experience running workloads built on large language models.
- Has built a backend platform from the ground up that supports an external, customer-facing product.
- A mix of experience in large technology companies and in early-stage or research settings.
- Currently a senior or staff-level individual contributor who still codes daily and owns an entire system.
- A degree in computer science or another highly technical STEM field from a top university.
Bonus points
- Familiarity with data pipelines, job scheduling or machine learning experimentation workflows.
- A track record of taking product infrastructure from nothing to substantial scale.
Benefits
Compensation and benefits
- Base salary: USD 200,000 to 300,000 per year
- Equity
Location and work model
- Palo Alto, CA, United States
- On-site, 5 days per week in office
- Full-time