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HUD is building infrastructure for reinforcement learning training data and evaluations for frontier AI agents, plus a marketplace to sell these services to frontier labs. The platform is used by frontier labs, Fortune 500 companies, and startups. The company has raised $16M from top VCs and was part of Y Combinator W25.
You will own the reliability, scale, performance, and developer experience of HUD's core infrastructure and backend systems. This is not a pure infrastructure role—the ideal candidate combines strong production infrastructure experience with backend engineering judgment. You'll work across AWS, Kubernetes, Terraform, CI/CD, observability, and backend services to make HUD faster, more reliable, cheaper to run, and easier for engineers to build on.
Key responsibilities include:
- Owning production uptime, latency, provisioning speed, infrastructure cost, and incident response for core platform services
- Building and maintaining AWS infrastructure with Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management
- Designing and improving backend and platform systems for scale, including capacity planning, autoscaling, queueing, backpressure, cleanup jobs, retries, and rollback paths
- Defining and improving dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows
- Building reliable CI/CD, release automation, environment management, and deployment workflows
- Writing clean, maintainable code to automate systems, improve backend services, and create internal tooling
The team is ~25 people, mostly full-time in-person but with some remote flexibility. The team includes 4 International Olympiad medalists, serial AI startup founders, and researchers with publications at ICLR and NeurIPS. The company has 8 figures in funding and is scaling profitably to meet strong demand.
REQUIREMENTS:
- Must have owned production cloud infrastructure for a high-availability, user-facing platform with responsibility for uptime, performance, deployment safety, and cost
- Deep experience with AWS infrastructure and containerized systems; strong preference for Terraform, Kubernetes/EKS, Docker, EC2, CodeBuild, ECR, S3, IAM, load balancers, networking, and secrets management
- Experience building or operating CI/CD, environment management, release automation, observability, alerting, and incident response systems
- Strong backend engineering judgment and ability to reason about service architecture, APIs, databases, async systems, queues, scaling limits, and production failure modes
- Ability to write clean, maintainable code and apply strong software engineering judgment across product architecture, infrastructure, backend systems, and developer workflows
Strong candidates may also have:
- Experience operating infrastructure for data-heavy, ML/AI, workflow, marketplace, developer-tools, or enterprise platforms
- Experience designing systems for bursty workloads, long-running jobs, sandboxed execution, distributed workers, or high-concurrency services
- Experience reducing cloud spend through better architecture, autoscaling, workload placement, caching, cleanup systems, or observability
- Experience building internal platforms or tools that make engineers faster without hiding too much complexity
The company prioritizes technical aptitude, ownership, and learning potential over years of experience. Full-time employment. Offices in San Francisco or Singapore; open to remote candidates who can work 70-80% overlap with either timezone. Visa sponsorship provided for strong candidates to US or Singapore.
