About the RoleWe'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 ForRequired:- 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.
