Platform Engineer

About the Role

This is a backend-architecture-heavy Platform Engineer role on a tight-knit engineering team of roughly 15 people, sitting at the intersection of reliability, scalability, and developer experience. You will own the core infrastructure that keeps a fast-moving AI/ML platform running at scale, making it faster, cheaper, and safer for the whole team to build and ship.

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, covering capacity planning, autoscaling, queueing, backpressure, cleanup jobs, retries, and rollback paths.
• Define and continuously improve dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows so failures are detected 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 code to automate systems, improve backend services, and create internal developer tooling.

What We're Looking For

• 2 to 4 years of experience owning production cloud infrastructure for a high-availability, user-facing platform, with direct responsibility for uptime, performance, deployment safety, and cost.
• Deep hands-on experience with AWS and containerized systems; strong familiarity with Terraform, Kubernetes/EKS, Docker, EC2, networking, load balancers, and secrets management.
• A track record of building or operating CI/CD, release automation, observability, alerting, and incident response systems.
• Strong backend engineering judgment across service architecture, APIs, databases, async systems, queues, and production failure modes.
• Experience designing systems for bursty workloads, long-running jobs, sandboxed execution, distributed workers, or high-concurrency services.
• Prior exposure to AI/ML platform engineering or software engineering in an AI/ML context; generic DevOps or infrastructure-only backgrounds are not a strong fit.
• Experience operating infrastructure for data-heavy, ML/AI, workflow, marketplace, developer-tools, or enterprise platforms is a plus.
• Demonstrated focus on reducing cloud spend through better architecture, autoscaling, workload placement, caching, or cleanup systems.
• High ownership mindset and genuine interest in learning; strong technical aptitude matters more than a specific number of years.

Compensation & Benefits

Salary range

$150,000 to $250,000 USD annually. Visa sponsorship is available.

Location

On-site in Singapore. Candidates based in San Francisco are also considered on-site there; fully remote arrangements are available for candidates based in Europe or other regions outside the US and Southeast Asia.