Staff Software Engineer

About the role

The role is focused on the development of software for the management of a fleet of GPU servers as well as the data centers that house those systems. The role focuses on the developing and implementing advanced diagnostic, observability, automation and repair tooling for high-performance GPU compute clusters.

Responsibilities

• Developing and implementing deep-level diagnostics and troubleshooting of hardware faults within GPU racks and high-density compute systems.
• Developing troubleshooting and automation tooling for GPU platforms including NVIDIA A100, H200, GB200, B200 and AMD 350X / 355X.
• Developing automation and AI agents for executing component-level diagnosis and remediation for failed or degraded hardware.
• In conjunction with data center operations, develop innovative tooling and AI agents for managing the critical environment.
• Developing tooling for post-repair validation and testing tools such as burn-in, Pytorch, and NVIDIA NCCL to ensure system stability and performance.
• Own the deployment, monitoring, and operational support of developed tooling, ensuring solutions maximize GPU fleet availability and performance to drive customer success.
• Developing automation and operational tooling for facilities management power as well as direct liquid cooling hardware systems.

Requirements

• Software engineering experience.
• The ability to identify a problem, rapidly develop a scalable solution and ship it.
• Ability to lean in and assist team members working on critical or complex technical initiatives.
• Ability to set the technical direction for a specific project and execute.
• Expertise in distributed systems, reliability, and cloud platforms (Kubernetes, IaC, GCP etc.).
• Strength in at least one programming language - Go, Python, Java, Rust.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.
• Able to work independently and within a team.

Qualifications

• Nice to have: Experience with Temporal and Kubernetes.
• Nice to have: Experience working directly with hardware vendors.
• Nice to have: Background in large-scale GPU fleet operations or hyperscale data center environments.

Skills

• Experience with distributed systems, reliability, and cloud platforms (Kubernetes, IaC, GCP etc.).
• Programming languages - Go, Python, Java, Rust.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.
• Ability to work independently and within a team.

Benefits

• Industry competitive pay.
• Restricted Stock Units in a fast growing, well-funded technology company.
• Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents.
• Employer contributions to HSA accounts.
• Paid Parental Leave.
• Paid life insurance, short-term and long-term disability.
• Teladoc.
• 401(k) with a 100% match up to 4% of salary.
• Grossly generous paid time off and holiday schedule.
• Cell phone reimbursement.
• Tuition reimbursement.
• Subscription to the Calm app.
• MetLife Legal.
• Company paid commuter benefit; $300 per month.

Pay

Compensation will be paid in the range of up to $208,000 - $253,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants knowledge, education, and abilities, as well as internal equity and alignment with market data.

Schedule

Not specified.