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IT

Senior Staff Software Engineer, Backend (Compute Platform)

Affirm
Location

Remote - United States (all states) · Remote

Type

Full-time

Level

Mid level

Posted

4 hours ago

Verified apply link — checked 2 hours ago

Salary undisclosed

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Before you apply

Job source
Ats
Applying on
job-boards.greenhouse.io
Workplace
Fully remote
US state
Nationwide remote
Category
IT
Link last checked
2 hours ago
Posted
4 hours ago
Closes
No stated closing date
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About the role

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Affirm's engineering team is building a large-scale, highly-available, and global infrastructure that is shared across multiple financial products. Ensuring that our infrastructure is accessible to all engineers is critical to the success of the business. We pride ourselves on our culture across engineering of engaging in thorough technical design review, operational excellence, and capable incident response and analysis. The Compute Platform team owns the EKS foundation that Affirm's products run on, from cluster provisioning and lifecycle through the safety standards that keep thousands of workloads reliable at scale. Affirm operates 90+ EKS clusters across environments and regions, and this team is responsible for making that fleet standardized, automated, observable, and self-healing, while establishing and enforcing the workload configuration standards that protect availability. Our mission is to provide a secure, reliable, and scalable Kubernetes platform that lets infrastructure and application teams deploy and operate with confidence and minimal operational friction. What you’ll do As a member of the Compute Platform organization, you will collaborate with other teams - including Product, Infrastructure, Traffic, Cost & Capacity Engineering to: Architect and evolve Affirm's EKS platform, driving strategy across cluster lifecycle, node management, and shared cluster components Lead the technical direction for cluster provisioning, upgrades, and teardown through standardized IaC (Terraform, Spacelift) and self-service workflows Own the reliability of core shared components across the fleet (Karpenter, CoreDNS, VPC CNI, Kube Proxy, Metrics Server, etc) and the CI/CD pipeline that ships them consistently Define and enforce EKS workload safety standards covering resource configuration, workload isolation and blast radius, disruption tolerance (PDBs), Karpenter consolidation strategies, etc Build the enforcement and automation path that moves each standard from research and white-glove onboarding through broad adoption to policy-enforced defaults for new workloads Establish the observability, baseline audits, and reporting needed to identify hot spots and measure risk mitigation over time Partner with cluster-user teams (checkout, batch, ML, analytics, DevProd, etc) to understand workload needs and shape the platform accordingly Drive cost and capacity strategy across node scaling, bin packing, and EC2 instance selection Mentor engineers across the Compute Platform teams and set the bar for operational excellence Participate in the on-call rotation, triage and catalogue runtime K8s issues, and collaborate with SRE on production incidents What we look for Deep EKS and Kubernetes internals expertise, including cluster upgrades, node lifecycle, scheduling, and autoscaling (Karpenter, Cluster Autoscaler) Demonstrated experience automating Kubernetes operations at fleet scale, from cluster provisioning, upgrades, and node lifecycle to self-healing remediation and policy-driven enforcement, replacing manual toil with auditable, self-service workflows Strong grasp of workload reliability patterns: resource tuning, probes, PDBs, topology and isolation constraints Experience designing and enforcing platform standards through policy (admission control, OPA/Gatekeeper or equivalent) and automated frameworks Infrastructure as Code fluency with Terraform and a GitOps or pipeline-driven delivery model (ArgoCD, kube-applier, or similar) Observability instincts: defining SLOs, building metrics, logs, and alerting coverage, and running data-driven baseline audits Cross-functional collaboration skills with platform, product, SRE, and capacity teams Demonstrated mentorship and technical leadership across teams Drive to track emerging Kubernetes community best prac

About Affirm

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