Senior Platform Engineer, Cloud (Xora Portfolio Company)
HybridSingapore, Singapore or San Diego, California, United States
Job Summary
Design and own the cloud infrastructure foundations including networking, identity, Kubernetes, and infrastructure-as-code that every service runs on. Build core platform services and internal APIs meant to operate reliably across customer-controlled environments, then instrument service-level objectives and health signals to ensure regressions are caught before they reach users. Stand up the observability layer with metrics, logs, traces, and alerting to make failing services quick to diagnose, while producing deployment-ready artifacts like container images and Helm charts for clean, repeatable installs. Harden the platform by managing secrets, certificates, and network boundaries to protect software and data wherever it lands. This role focuses on building reproducible, measurable foundations for an early-stage startup developing applied intelligence at the intersection of AI, physics, and large-scale computation.
Required Qualifications
- Bachelor's or Master's degree in Computer Science or a related engineering field
- 6+ years building and shipping production software
- real depth in cloud infrastructure and platform engineering
- Deep hands-on experience building cloud infrastructure with Kubernetes and infrastructure-as-code (Terraform or similar)
- experience on at least one major cloud (AWS, GCP, or Azure)
- Experience designing and operating core backend services and APIs
- Direct ownership of a cloud deployment process: build and release pipelines, versioned artifacts, and safe, reproducible rollouts
- Hands-on experience building observability into production systems (metrics, logs, and traces)
- Strong software-engineering fundamentals and hands-on coding in a systems or backend language (Go, Python, Rust, or similar)
- Experience defining service-level objectives and designing for reliability
- Comfort building foundational systems others depend on in an early-stage, ambiguous environment
Desired Qualifications
- Experience building platform components that run across varied deployment environments, including customer-controlled ones
- Experience running workloads across more than one runtime: cloud Kubernetes plus HPC schedulers (Slurm or similar) or bare metal
- GPU scheduling or multi-tenant cluster experience
- GitOps and progressive-delivery patterns (ArgoCD, Flux, staged rollouts)
- Experience packaging or serving ML models, or supporting ML and data workloads on a shared platform
- Exposure to scientific computing, simulation, or other large-scale technical workloads
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