Platform Engineer

About the Role

We're a fast-growing AI/ML platform startup building infrastructure for training, evaluating, and aligning AI models within reinforcement learning environments. Our engineering team of ~15 includes competitive programming medalists, serial AI startup founders, and researchers published at top venues — and we're looking for a Platform Engineer to own the reliability, scale, performance, and developer experience of our core infrastructure.

This is a backend-architecture-heavy role with high ownership. Your work will directly determine how fast, reliable, and cost-effective our platform is to build on and run.

What You'll Do

• Own production uptime, latency, provisioning speed, infrastructure cost, and incident response for core platform services.

• Build and maintain AWS infrastructure using Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management.

• Design and improve backend and platform systems for scale — 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 pipelines, release automation, environment management, and deployment workflows that improve developer productivity and reduce production risk.

• Write clean, maintainable production code to automate systems, improve backend services, and create internal developer tooling.

What We're Looking For

Required:

• 2–4 years of experience owning production cloud infrastructure for a high-availability, user-facing platform, with accountability for uptime, performance, deployment safety, and cost.

• Deep hands-on experience with AWS and containerized systems; strong familiarity with Terraform, Kubernetes/EKS, Docker, EC2, load balancers, networking, and secrets management.

• Track record of building or operating CI/CD, release automation, observability, alerting, and incident response systems.

• Strong backend engineering judgment — able to reason about service architecture, APIs, databases, async systems, queues, scaling limits, and production failure modes.

• Ability to write production-quality code to automate infrastructure, improve backend services, and build internal tooling.

Nice to Have:

• Experience designing systems for bursty workloads, long-running jobs, sandboxed execution, distributed workers, or high-concurrency services.

• Background operating infrastructure for data-heavy, ML/AI, workflow, marketplace, developer-tools, or enterprise platforms.

• Demonstrated focus on reducing cloud spend through better architecture, autoscaling, workload placement, caching, or cleanup systems.

• Experience building internal platforms or developer tools that improve engineering productivity without hiding complexity.

We prioritize technical aptitude, ownership, and learning potential over years of experience.

Location

• San Francisco, CA (on-site): US-based candidates must be located in San Francisco.

• Singapore (on-site): Southeast Asia-based candidates must be located in Singapore.

• Fully remote (contractor): Candidates based elsewhere — particularly in Europe — may be considered as fully remote independent contractors.

Visa sponsorship is available.

Compensation & Benefits

• Salary: $150,000 – $250,000 USD annually (for full-time roles)

• Opportunity to have significant ownership and direct impact at an early-stage, well-funded AI infrastructure company.

• Work alongside a world-class technical team building foundational infrastructure for AI alignment and post-training data.