Software Engineer (Infrastructure)

Join our team as a Software Engineer (Infrastructure) and take ownership of our platform, including GCP, Kubernetes, Temporal, and our GPU fleet. You will be responsible for the AI enablement substrate, cost management, security, and improving team learning and shipping practices. You will also provide architectural direction, mentoring, and clear communication. Enjoy benefits such as health coverage, retirement plans, flexible time off, parental leave, a home-office stipend, and annual off-site gatherings.

Intricacies of Video: Media, video, or GPU-backed workloads

About Descript

You've run systems where failure was expensive, and your opinions about reliability and deployment come from consequences rather than reading

Responsibilities

• Posséder et gérer notre plateforme, y compris GCP, Kubernetes, Temporal, et la flotte GPU.
• Être responsable de l'infrastructure permettant l'activation de l'IA, y compris la capacité GPU et les pipelines d'entraînement.
• Prendre des décisions éclairées sur les coûts liés à l'infrastructure et à l'utilisation des ressources.
• You use SLOs and error budgets as operating tools
• You've owned an architecture or migration, from planning through launch, whose consequences outlived the project, and you can say what you'd do differently
• You've carried a pager, commanded an incident, and rolled back before you understood why
• GPU and ML infrastructure: capacity planning, training or inference pipelines, serving cost and latency. If you haven't run a GPU fleet, experience with expensive capacity-constrained systems transfers well
• Cloud cost modeling: commitment strategy, reservations, unit economics

Requirements

• You build a minimal repro, read the logs, and write targeted checks to prove a fix works instead of trusting output
• You have 8+ years building and operating production distributed systems, or equivalent server-side engineering with a heavy infrastructure focus
• You effectively leverage agents to multiply your impact and think critically about how and when to harness AI in your work
• You’ve used a major cloud provider and Kubernetes in production, with infrastructure-as-code as your default
• You've found important unowned work, scoped it, earned buy-in, and delivered it without being handed a spec
• Production security engineering: IAM, secrets, supply chain, least privilege. You don't need to have held a security title, but you should have owned these boundaries for systems you ran
• CI/CD: at monorepo scale, and developer-environment work
• Small teams owning a large surface: whether at a Series B to D company or on an internal platform team

Pay

USD 220,000 - 292,000