Persona Identities
Senior Software Engineer, Compute
San Francisco · Senior · Contract
Sponsorship not specifiedDetected 57 days ago
RubyRailsDistributed SystemsKubernetesTerraform
About the role
- What matters most is product instinct: understanding your users (product engineers), measuring whether they're getting unblocked, and treating developer experience as a feature acceptance criterion.
- When ArgoCD fails and every team's deploy is blocked, that's your page.
- The team is still establishing its patterns, and you'll have real influence over what they become.
Responsibilities
- Build internal platform tooling and APIs that product engineers use to deploy, scale, and observe services, with developer experience as a first-class requirement
- Own and evolve the Kubernetes platform, ArgoCD deployment pipeline, and Terraform IaC that underpin every service at Persona
- Drive Cloud Run-to-Kubernetes migration, working directly with product teams to remove blockers and hand off operational ownership cleanly
- Design self-service workflows to reduce the Compute interrupt load. Success means product engineers can do more without filing a ticket.
- platform APIs, internal tooling, deployment pipelines, automation that replaces the support tickets.
Requirements
- any engineer, using AI, should be able to stand up and operate a stateful service at production scale with no meaningful infrastructure knowledge required.
- The Compute team's mission: any engineer, using AI, should be able to stand up and operate a stateful service at production scale with no meaningful infrastructure knowledge required.
Company info
- Persona is the configurable identity platform built for businesses in a digital-first world.
- We've built Persona to support practically every use case and industry - that's why we're able to serve a wide range of leading companies.
- As part of our interview process, all candidates will be asked to verify their identity with Persona.
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This listing is sourced directly from Persona Identities's careers page and normalized into a canonical job model.