Agentic AI infrastructure powering regional banks and member-owned credit unions
Staff Platform and Reliability Engineer
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Your mornings start where voice calls hit the rail, where Kubernetes nodes groan under inference load, and where a slow S3 bucket means a loan officer somewhere is staring at a spinning wheel. You'll redesign our AWS estate for a team that ships TypeScript services into production multiple times a day, and you'll build the guardrails that let that velocity coexist with SOC 2, FFIEC, and the paranoia that regulators and community bankers rightly share. Some days that means writing a Python operator to autoscale GPU workloads; others, it's sitting with an ML engineer to debug why a single AZ failure cascaded into dropped intent classification. The San Francisco office is where this lives—whiteboards, post-mortems, the occasional 7 p.m. deploy rollback.
What they're looking for
- Five or more years running production AWS infrastructure at scale, with Kubernetes as your primary orchestration layer
- Proficiency in both TypeScript and Python—not just stitching together Lambdas, but building internal platforms other engineers adopt willingly
- Demonstrated ownership of incident response, SLO definition, and blameless post-mortem culture in regulated or high-stakes environments
- Experience with cost-aware architecture: right-sizing compute, negotiating reserved capacity, and making tradeoffs visible to leadership
- Deep curiosity about AI serving patterns—caching embeddings, batching inference requests, and reasoning about tail latency in conversational systems