Senior Platform Engineer

Level: Senior

Location: San Francisco, CA — Onsite

Type: Full-Time

Reports to: Engineering Manager, Platform

ABOUT READYON

ReadyOn is an AI-native workforce management SaaS platform operating at enterprise scale. Our infrastructure is multi-tenant, cloud-native, and built for reliability across thousands of locations globally. The platform team owns the full infrastructure lifecycle — design, build, operate, improve — and operates with a high degree of autonomy.

Agentic coding and AI-assisted development are core to how we work. We use them to move faster, generate infrastructure automation, and reduce toil. We expect senior engineers to lead by example here — pushing the ceiling on what's possible when you combine deep infrastructure expertise with modern AI tooling.

THE ROLE

We're looking for a Senior Platform Engineer / SRE who can set the standard for how we automate and operate systems at scale. You'll tackle hard problems — multi-tenant isolation, self-service infrastructure, reliability engineering — and have the scope to solve them properly.

This is not a ticket-processing role. Seniors here identify problems before they're asked, and raise the ceiling on what the platform can do.

WHAT YOU'LL WORK ON

• Shape how we do infrastructure-as-code — Terraform patterns, multi-account design, and the standards that hold it together across teams.

• Operate GitOps at scale — ArgoCD configuration, managing promotion workflows, and ensuring deployment reliability across multiple environments and tenants.

• Operate multi-tenant Kubernetes infrastructure on AWS EKS — managing tenant isolation, workload placement, cluster topology, and maintaining scalability.

• Maintain self-service infrastructure automation — managing provisioning pipelines and configuration management.

• Use agentic coding tools for infrastructure work — scaffolding new environments, generating and reviewing IaC, and accelerating automation.

• Own reliability — managing SLOs, monitoring error budgets, ensuring incident response quality, and driving the feedback loop that turns incidents into platform improvements.

• Maintain observability standards — ensuring trace coverage, alert quality, on-call ergonomics, and runbook culture.

• Maintain security posture — focusing on secrets management at scale and infrastructure hardening.

MUST HAVE

• 5+ years in platform engineering, SRE, or infrastructure — with meaningful time operating production systems at scale.

• Deep IaC expertise — you actively manage complex Terraform state and multi-account configurations in production.

• Strong GitOps background — you understand declarative infrastructure management at depth and have opinions on how to do it well.

• Deep Kubernetes knowledge — you've operated clusters in production, dealt with real failure modes, and understand the system at the control plane level.

• Strong AWS background — networking, compute, IAM, storage, multi-account design

• Automation-first thinking at a senior level — you implement systems that eliminate entire categories of manual work.

• Hands-on experience building and operating CI pipelines — GitHub Actions, CircleCI, GitLab CI, or equivalent.

• Active user of agentic coding tools — you know how to direct them effectively, review their output critically, and use them to multiply your output.

• Reliability engineering track record — SLOs defined and measured, post-mortems run, measurable improvements driven.

• Strong communicator — you can articulate operational decisions and incident summaries clearly to engineers and leadership alike.

NICE TO HAVE

• Experience with Keycloak or other IdP

• Experience with Argo: ArgoCD, Argo Workflows, Rollout

• Experience with Karpenter and node lifecycle management in production

• Background in FinOps — cost attribution, reserved capacity planning, workload right-sizing

• Familiarity with data infrastructure — object storage, CDC pipelines, or lakehouse patterns

• Experience with multi-tenant infrastructure — isolation patterns, noisy neighbor mitigation, and tenant lifecycle management.

• Experience supporting AI/ML inference workloads or GPU-based compute in production

• Prior experience scaling platform infrastructure at a startup moving toward enterprise-grade requirements

WHAT YOU WON'T FIND HERE

A platform team that maintains the status quo. We're actively building — new scale requirements, new architectural domains, new automation capabilities. Senior engineers here shape how the platform evolves, and the tools available to do it are better than they've ever been.