Software Engineer, Infrastructure

Descript; United States; Remote; USD 220,000 - 292,000; Full time

Benefits offered by this job

Healthcare package

401k matching

Catered lunches

Flexible vacation

Job summary

Descript is seeking an experienced platform engineer to own and scale production infrastructure across GCP, Kubernetes, Temporal, and our GPU fleet powering model training and serving. You’ll participate in on-call rotations and drive cost-aware decisions to keep systems reliable and efficient.

You will collaborate with multiple engineering teams to shape reliability, observability, IaC practices, and tooling.

Qualifications

• 8+ years building and operating production distributed systems or equivalent server-side engineering with a heavy infrastructure focus.
• You effectively leverage agents to multiply impact and think about how/when to harness AI in work.
• Experience with reliability and deployment consequences from real incidents.

Responsibilities

• Own our platform: GCP, Kubernetes, Temporal, the GPU fleet behind cloud export, and deployment/rollback machinery.
• Be in the on-call rotation and make it quieter and more actionable.

Skills

Distributed systems

Kubernetes

GCP

Temporal

GPU infrastructure

Infrastructure as code

CI/CD

SRE practices

Cost modeling

Security engineering

Tools

Terraform

GitHub Actions

Monorepo tooling

Cloud logging/monitoring

Job description

Headquarters: San Francisco, CA or Remote, US

Platform owns the foundation the company runs on: compute and deployment, reliability and on-call, CI/CD and monorepo health, developer environments, the infrastructure that model training and inference run on, and the security boundaries around all of it.

AI and agent tooling is the clearest example. You will contribute to how models are trained and served here, as well as how agents work inside our codebase: the environments they run in, the verification that makes their output trustworthy, and the review paths that keep it all legible. There is no industry standard and you’ll help form our opinions rather than inheriting one.

Our users are other engineers. Expect to spend time with all the other engineering teams, understanding their needs and building a roadmap. The scope is large, so you'll be choosing what to leave alone as much as build.

Architecture decisions here last: this is a small team covering a large surface. You'll have real room to decide things, and you'll stay close to the systems you decide about.

What you'll ownOwn our platform: GCP, Kubernetes, Temporal, the GPU fleet behind cloud export, and the deploy and rollback machinery everything ships through. You'll be in the on-call rotation, and we'll expect you to make it quieter and more actionable.The AI enablement substrate: GPU capacity, training and inference pipelines, and the reliability and cost of the systems serving models in production.Cost is an engineering constraint: infrastructure decisions have a number attached and you're expected to make smart trade-offs. As inference grows with usage, the metering and attribution behind those numbers sit with this team.Security comes with the systems you run : identity and access, secrets management, least-privilege boundaries, and supply-chain integrity.Make what you build legible. Infrastructure-as-code that explains itself. Runbooks and in-repo context written for someone jumping in to help. Observability that tells you what failed and why.Improve how the team learns and ships. Form hypotheses, instrument your work, release incrementally, and read results honestly. Strengthen the tooling, standards, tests, observability, and release practices that help the team move quickly without compromising quality.Raise the team’s technical ambition. Provide architectural direction, thoughtful reviews, mentoring, and clear human writing.

What you bringRequired:

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 run systems where failure was expensive, and your opinions about reliability and deployment come from consequences rather than reading.You've carried a pager, commanded an incident, and rolled back before you understood why.You use SLOs and error budgets as operating tools.You’ve used a major cloud provider and Kubernetes in production, with infrastructure-as-code as your default.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 found important unowned work, scoped it, earned buy-in, and delivered it without being handed a spec.You build a minimal repro, read the logs, and write targeted checks to prove a fix works instead of trusting output.Experience that helps:

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.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.Cloud cost modeling: commitment strategy, reservations, unit economics.CI/CD: at monorepo scale, and developer-environment work.Intricacies of Video: Media, video, or GPU-backed workloads.Small teams owning a large surface: whether at a Series B to D company or on an internal platform team.the company is a startup. We’re especially interested in working with engineers who use the product and are aligned with our mission. To that end, we promise to review any application that includes a share link to a the company video. The video can be about anything - your career, a favorite game or movie, a discarded audition tape for Love Island. If you take the time to make something in the company, we’ll commit to having a human watch it and review your application.

Compensation and benefitsBase salary: $220,000 to $292,000, plus equity and benefits. Final offer amounts will carefully consider multiple factors, including prior experience, expertise, location, and level, and may vary from the amount above.

About the companythe company is building a simple, intuitive, fully-powered editing tool for video and audio — an editing tool built for the age of AI. We are a team of 150 and the backing of some of the world's greatest investors ( OpenAI , Andreessen Horowitz , Redpoint Ventures , Spark Capital ).

the company is the special company that's in possession of both product market fit and the raw materials (passionate user community, great product, large market) for growth, but is still early enough that each new employee has a measurable influence on the direction of the company.

Benefits include a generous healthcare package, 401k matching program, catered lunches, and flexible vacation time. Our headquarters are located in the Mission District of San Francisco, CA. We're hiring for a mix of remote roles and hybrid roles. For those who are remote, we have a handful of opportunities throughout the year for in person collaboration. For our hybrid roles, we're flexible, and you're an adult—we don't expect or mandate that you're in the office every day. We do believe there are valuable and serendipitous moments of discovery and collaboration that come from working together in person.

the company is an equal opportunity workplace—we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We believe in actively building a team rich in diverse backgrounds, experiences, and opinions to better allow our employees, products, and community to thrive.