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.