Senior Software Engineer, Backend (Workload Safety)
Affirm is hiring a Senior Software Engineer, Backend (Workload Safety) for a remote role open to applicants in United States. It pays $195k-$255k a year and Level rates it ; you can apply on Affirm.
Level's read on this job
- Little AI ●○○○ is how Level rates this software engineer role: aI is not part of the work.
- Pay on this posting starts 16% higher than the typical software engineer posting on Level.
- This is listed as a remote role.
- The posting mentions Kubernetes, AWS and Karpenter among its tools and skills.
- Affirm has 224 other open roles on Level.
AI in this role
Define and enforce workload safety standards across Affirm's Amazon EKS cluster fleet to ensure high availability and performance.
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
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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
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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
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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
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Isolate workloads by criticality and resource profile so one misbehaving workload cannot degrade critical paths such as checkout
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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
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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
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Analyze workload resource profiles across the fleet (CPU, memory, disk, network) to guide EC2 instance type strategy, and automate that analysis as workloads change
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Measure each standard's impact on availability, latency, risk, and cost, and use the results to prioritize the roadmap
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Participate in on-call for Kubernetes runtime issues across the fleet, and turn recurring failure patterns into roadmap items
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Work closely with the teams that run services, batch jobs, and ML workloads on EKS, and with the deployment, capacity, and SRE teams
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Keep up with new best practices from the Kubernetes community and adapt them to Affirm's needs
What we look for
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5+ years of experience running Kubernetes in production at scale, ideally Amazon EKS across many clusters
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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
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Solid grasp of the pod lifecycle and disruption management, including graceful termination, pod disruption budgets, and node draining
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Experience enforcing configuration standards through admission control and policy-as-code (for example, OPA Gatekeeper or Kyverno)
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Proficiency in Go or Python, including building production infrastructure software such as Kubernetes controllers, operators, or admission webhooks
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Strong production debugging skills and a demonstrated ability to turn recurring incidents into systemic fixes
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Track record of leading technical initiatives across multiple teams, driving adoption of shared standards, and mentoring other engineers
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Experience quantifying the impact of infrastructure changes on availability, latency, and cost
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Strong written communication, including standards and guidance that teams can adopt on their own
- This position requires either equivalent practical experience or a Bachelor’s degree in a related field.
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:
- Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
- Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
- Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
- Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.
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.
By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.
How we rate this
Senior Software Engineer, Backend (Workload Safety) at Affirm rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $195k
- Typical software engineer job
- $168k
This posting starts 16% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- What's a project where you used Kubernetes hands-on?
- Walk me through how you've used AWS in your day-to-day work.
- What are the limits of Karpenter that you've run into, and how did you work around them?
Adapt your resume
- List these exact terms on your resume: Kubernetes, AWS, and Karpenter. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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