Staff Platform Engineer (Infrastructure)

Staff Platform Engineer (Infrastructure)

We are seeking an experienced Staff Platform Engineer to help build and operate Acorn, Postscript's next-generation CDP and messaging platform: ~52 Rust/Python services on EKS, built to run at 500K+ events/sec for 20K+ merchants.

What makes this role different: the platform is agent-operated . Deploys, migrations, drift reconciliation, and infra standup are automated and encoded as self-verifying runbooks that AI agents execute. We are not hiring someone to run those procedures by hand. We are hiring the person who designs the system, writes the guardrails that let agents execute it safely, and owns the failures no runbook covers yet.

Primary duties

• System & Platform Design: Own infra topology, scaling and blast-radius boundaries, the build/deploy graph, database ownership boundaries, and cost ceilings — the decisions agents execute but can't make.
• Guardrail Engineering: Build the validation gates, idempotency checks, drift detectors, and runbooks that keep both humans and agents from doing damage. Your deliverable is the safety system, not the deploy.
• Escalation Tier: Diagnose the novel failures — consumer lag, DLQs, materialized-view chains, consent ordering. Write the runbook the first time; agents handle it after.
• Reliability, Capacity & Cost: Own the 500K events/sec target: load testing, Karpenter/HPA tuning, Database sizing, SLOs and alerting.
• Security & Secrets Boundary: Own IAM/IRSA, secret rotation, the auth chain, and what the agent/MCP surface is allowed to do.
• Agent-Fleet Operability: Keep skills, runbooks, and agent context in sync with reality. A stale runbook is a wrong actor, executed confidently.
• Incident Leadership: Lead incidents and capture every fix as a new runbook plus regression test.

What We’ll Love About You

• Experience: 5+ years operating production Kubernetes and cloud infrastructure (AWS) at scale.
• IaC Discipline: Strong Terraform and GitOps/Kustomize practice, with a bias for making operations idempotent, automated, and self-verifying.
• Incident Judgment: Real incident-response experience on distributed-systems failures — databases, streaming, consumer lag, data integrity.
• Data Systems Fluency: You know how Postgres, a columnar store, and a log/streaming bus behave under load.
• Agent Fluency: Comfort working alongside AI agents — writing the guardrails, runbooks, and checks that let automation operate safely, and knowing where a human must stay in the loop.
• Instincts: You reach for 'encode this as a check' before 'I'll remember to do this.' You'd rather delete a manual step than document it. You treat a wrong runbook as a production bug.