About the Role
This is a backend-architecture-heavy platform engineering role sitting within a tight-knit engineering team of roughly 15 people. You will own the reliability, scale, performance, and developer experience of core infrastructure and systems for an AI/ML evaluation and reinforcement learning platform. The work has direct, measurable impact on how fast, reliable, and cost-effective the platform is to build on and operate.
What You'll Do
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Own production uptime, latency, provisioning speed, infrastructure cost, and incident response for core platform services.
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Build and maintain AWS infrastructure using Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management.
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Design and improve backend and platform systems for scale, covering capacity planning, autoscaling, queueing, backpressure, cleanup jobs, retries, and rollback paths.
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Define and improve dashboards, alerts, logs, traces, SLOs, runbooks, and on-call workflows so failures are detected, debugged, and resolved quickly.
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Build reliable CI/CD pipelines, release automation, environment management, and deployment workflows that improve developer productivity and reduce production risk.
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Write clean, maintainable code to automate systems, improve backend services, and create internal developer tooling.
What We're Looking For
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2 to 4 years of experience owning production cloud infrastructure for a high-availability, user-facing platform, with responsibility for uptime, performance, deployment safety, and cost.
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Deep hands-on experience with AWS and containerized systems; Terraform, Kubernetes/EKS, Docker, EC2, networking, load balancers, and secrets management strongly preferred.
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A track record of building or operating CI/CD, release automation, observability, alerting, and incident response systems.
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Strong backend engineering judgment across service architecture, APIs, databases, async systems, queues, scaling limits, and production failure modes.
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Experience designing systems for bursty workloads, long-running jobs, sandboxed execution, distributed workers, or high-concurrency services.
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Background operating infrastructure for AI/ML, data-heavy, marketplace, workflow, developer-tools, or enterprise platforms.
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Demonstrated focus on reducing cloud spend through better architecture, autoscaling, workload placement, caching, cleanup systems, or observability.
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Ability to write clean, production-quality code; generic DevOps or infrastructure-only backgrounds without backend software engineering depth are not a strong fit.
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 for on-site work there. Candidates outside these locations, particularly in Europe, may be considered as fully remote independent contractors.
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