Software Engineer

Who you are

• 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
• 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

What the job involves

• Own 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

Benefits

• Health: We’ve got you covered with medical, dental, and vision benefits for all employees and their dependents. These include HMO and PPO healthcare plans.
• Retirement: We offer a variety of retirement plans, including employer matching. Not exciting to talk about, but the match is competitive and the plans are good.
• Time off: Paid holidays are a given, but you can also expect flexible time off. Feel comfortable to take the time you need, when you need it.
• Parental leave: New parents receive paid parental leave to spend quality time with their expanding families.
• Home-office stipend: Get your work-from-home setup ready with our home-office stipend.
• Destination off-sites: No matter where you decide to work, you’ll get to know your team at our annual off-site gatherings.