Staff Platform & Reliability Engineer

Responsibilities

• Define customer-facing SLIs and SLOs, operate error budgets, and govern release decisions through reliability targets.
• Own regional failover, disaster recovery, RTO/RPO definitions, third-party dependency resilience, and tested recovery procedures.
• Build and operate GitOps-based progressive delivery with automated analysis, one-click rollback, drift detection, and change auditing.
• Own AWS infrastructure-as-code, Kubernetes, service mesh, capacity, cost, and scale across the platform.
• Lead paging, severity policies, incident-command rotations, status-page automation, post-mortems, and customer SLA reporting.
• Build metrics, logging, distributed tracing, dashboards, alerts, and burn-rate alerting as code.
• Develop AI-native operational automation, safe runbooks, self-healing workflows, and golden-path service templates.
• Own cloud and cluster security, including IAM least privilege, secrets management, admission and network policy, image signing, SBOMs, scanning, and threat-detection feeds.
• Produce infrastructure compliance evidence for SOC 2 Type II, NCUA/FFIEC examinations, and GLBA reviews.
• Protect AI systems against prompt injection, tool-based data exfiltration, tenant-isolation failures, endpoint abuse, and unsafe AI-assisted engineering workflows.

Requirements

• Senior-most hands-on individual contributor experience running production systems with real uptime commitments and pager participation.
• Deep production Kubernetes on AWS, including service mesh and GitOps delivery across many services.
• Experience managing infrastructure-as-code at multi-account scale and reshaping large existing estates.
• Experience building SLO and error-budget practices, burn-rate alerting, and multi-region or disaster-recovery capabilities with tested failover.
• Daily-practice security experience with least-privilege IAM, secrets management, admission and network policies, software supply-chain controls, and auditor-facing evidence.
• Daily fluency with frontier AI tools such as Claude Code and Cursor, including judgment about agent operating boundaries.
• Strong programming ability in TypeScript and/or Python plus Bash, with clear technical and regulatory-facing writing.
• BS or BA in Computer Science required; an MS or PhD is preferred.
• Preferred experience includes real-time voice or telephony systems, streaming or analytical data platforms, durable workflow engines, chaos engineering, regulated industries, LLM threat modeling, cloud cost engineering, and LLM spend attribution.
• Must be San Francisco-based, committed to working onsite, and able to participate in on-call coverage.

Benefits

• 100% paid health, dental, and vision care.
• 401(k), financial wellness perks, daily meals, commuter benefit, monthly wellness stipend, and mental health, wellness, and family benefits.
• Claude Enterprise and frontier AI tools for every employee.
• Discretionary PTO and paid parental leave.
• Onsite work at the brand-new 21st-floor San Francisco office at 44 Montgomery.