Platform Engineer

About HUD

HUD is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs through the HUD marketplace. Our platform is used by frontier labs, Fortune 500 companies, and startups. We’ve raised $16M from top VCs and were YC W25.

About The Role

We’re looking for a platform engineer who can own the reliability, scale, performance, and developer experience of HUD’s core infrastructure and backend systems. This is not a pure infrastructure role. The right person has strong production infra experience, but also thinks like a backend engineer: they can reason about service architecture, queues, databases, APIs, deployment safety, performance bottlenecks, and how product requirements translate into resilient systems. 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.

Responsibilities

• Own production uptime, latency, provisioning speed, infrastructure cost, and incident response for core platform services
• Build and maintain AWS infrastructure with Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management
• Design and improve backend and platform systems for scale, including capacity planning, autoscaling, queueing, backpressure, cleanup jobs, retries, and rollback paths
• Define and improve dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows so failures are detected, debugged, and resolved quickly
• Build reliable CI/CD, release automation, environment management, and deployment workflows that improve developer productivity and reduce production risk
• Write clean, maintainable code where needed to automate systems, improve backend services, and create internal tooling

Experience

• Have owned production cloud infrastructure for a high-availability, user-facing platform, with responsibility for uptime, performance, deployment safety, and cost
• Have deep experience with AWS infrastructure and containerized systems; experience with tools like Terraform, Kubernetes/EKS, Docker, EC2, CodeBuild, ECR, S3, IAM, load balancers, networking, and secrets management is strongly preferred
• Have built or operated CI/CD, environment management, release automation, observability, alerting, and incident response systems
• Have strong backend engineering judgment and can reason about service architecture, APIs, databases, async systems, queues, scaling limits, and production failure modes
• Can 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