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Clera Labs, Inc. is seeking a backend-focused Platform Engineer to own the reliability, scale, and observability of our AI infrastructure. You’ll build and operate AWS-based systems using Terraform, Kubernetes/EKS, Helm, Docker, and related tools, while driving incident response and deployment automation.
You’ll collaborate with a small engineering team in Singapore to improve performance, control costs, and deliver robust runbooks, dashboards, and on-call workflows that keep production healthy.
Join a small engineering team building infrastructure for AI model training and evaluation. In this backend-focused role, you will own the reliability, scale, performance, and developer experience of core platform systems.
Own uptime, latency, provisioning speed, infrastructure costs, and incident response for production platform services.
Build and maintain AWS infrastructure using Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management.
Improve systems for scale through capacity planning, autoscaling, queueing, backpressure, cleanup jobs, retries, and rollback paths.
Develop dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows to help teams detect and resolve failures quickly.
Build CI/CD, release automation, environment management, and safe deployment workflows that improve developer productivity.
Write production code to automate infrastructure, improve backend services, and build internal tools.
At least 2 years of experience in platform engineering, backend engineering, or infrastructure roles operating production cloud systems.
Strong technical fundamentals and production experience with AWS and containerized systems, especially Terraform, Kubernetes/EKS, Docker, networking, load balancers, and secrets management.
Experience owning reliability and incident response, and building CI/CD, deployment automation, and observability systems.
Sound backend judgment across service architecture, APIs, databases, asynchronous systems, and production failure modes.
AI/ML platform or software engineering experience, ideally involving data-heavy systems, bursty workloads, long-running jobs, sandboxed execution, or distributed workers.
Ability to write maintainable production code and improve infrastructure efficiency through architecture, autoscaling, workload placement, caching, or cleanup systems.
Base salary: $100,000 to $170,000 USD annually. Visa sponsorship is available.
On-site in Singapore, Singapore.