Senior Software Engineer, Backend (Workload Safety)

At Affir​m, 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.

Affir​m'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.

Affir​m 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 Affir​m can grow globally and still meet its availability and latency SLOs. The team identifies the industry best practices Affir​m 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 Affir​m'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 Affir​m'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

This posting is for an existing vacancy.

Pay Grade

N

Equity Grade

6

Employees new to Affir​m typically come in at the start of the pay range. Affir​m 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 monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affir​m Holdings, Inc. (parent company).

CAN base pay range per year: CAD $153,000 - $213,000.

Location - Remote Canada

This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan.

Remote-first with flexibility built in

Affir​m 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 Affir​m 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

• 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 Affir​m 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: Affir​m considers qualified applicants with arrest and conviction records, as required by law.