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.