Remote, Oregon, United States
Remote only
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.
Affirm runs its workloads on more than 85 Amazon EKS clusters, and the number is growing. The Workload Safety team creates one set of standards for how workloads are configured and run, so Affirm can grow globally and still meet its availability and latency SLOs. The team identifies the industry best practices Affirm needs, drives their adoption across every engineering team on EKS, and enforces them through policy and automation so new workloads comply by default.
As a senior engineer on the team, you will help set its roadmap, decide which standards matter most, and build a repeatable way to take each standard from research to enforcement across the fleet.
What you’ll do
Define and evolve workload safety standards for Affirm's EKS fleet, such as CPU and memory settings, workload isolation and placement, tolerance for disruption, graceful termination to name a few
Own each standard end to end: research and prototyping, white-glove onboarding for early adopters, self-service guidance for everyone else, and automation and policy guardrails that keep every workload compliant from day one
Lead cross-team initiatives from design through fleet-wide rollout, mentor other engineers, and set a high bar for design, code review, and operational readiness
Isolate workloads by criticality and resource profile so one misbehaving workload cannot degrade critical paths such as checkout
Fix stuck workloads and node lifecycle problems, such as pods that ignore termination signals, pod disruption budgets that block node cycling, and Karpenter timeouts that prevent bin packing and the removal of excess capacity
Determine the safe operating limits of each cluster (pod count, node count, API server request volume), keep clusters within them, and develop control plane scaling patterns for bursty workloads such as scheduled batch jobs and large deployments
Analyze workload resource profiles across the fleet (CPU, memory, disk, network) to guide EC2 instance type strategy, and automate that analysis as workloads change
Measure each standard's impact on availability, latency, risk, and cost, and use the results to prioritize the roadmap
Participate in on-call for Kubernetes runtime issues across the fleet, and turn recurring failure patterns into roadmap items
Work closely with the teams that run services, batch jobs, and ML workloads on EKS, and with the deployment, capacity, and SRE teams
Keep up with new best practices from the Kubernetes community and adapt them to Affirm's needs
What we look for
5+ years of experience running Kubernetes in production at scale, ideally Amazon EKS across many clusters
Deep understanding of Kubernetes resource management and scheduling: requests and limits, OOM and CPU throttling behavior, affinity and anti-affinity, taints and tolerations, and topology spread constraints
Solid grasp of the pod lifecycle and disruption management, including graceful termination, pod disruption budgets, and node draining
Experience enforcing configuration standards through admission control and policy-as-code (for example, OPA Gatekeeper or Kyverno)
Proficiency in Go or Python, including building production infrastructure software such as Kubernetes controllers, operators, or admission webhooks
Strong production debugging skills and a demonstrated ability to turn recurring incidents into systemic fixes
Track record of leading technical initiatives across multiple teams, driving adoption of shared standards, and mentoring other engineers
Experience quantifying the impact of infrastructure changes on availability, latency, and cost
Strong written communication, including standards and guidance that teams can adopt on their own
Pay Grade - N
Equity Grade - 9
Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)
USA base pay range (CA, WA, NY, NJ, CT) per year: $195000 - $255000
USA base pay range (all other U.S. states) per year: $173000 - $233000
#LI-Remote
Remote-first with flexibility built in
Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.
Benefits designed for you
Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:
We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.
For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.
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