Staff Engineer - Cloud Platform Engineering

About the Role: We are looking for a Staff Engineer to join our Cloud Platform team and take deep ownership of key platform systems within our multi-tenant SaaS infrastructure. You will work at the intersection of backend engineering and cloud infrastructure — designing, building, and operating the systems that power our control plane and data plane at scale. This is a high-impact, hands-on role.

You will be a technical leader within the team — driving design decisions for significant platform initiatives, growing engineers around you, and partnering with senior engineers and product leads to ship reliable, scalable platform capabilities. What You Will Do: Architecture & Design • Lead architecture and design for significant platform subsystems spanning control plane and data plane • Design and implement multi-tenant components with strong isolation, security, and resource governance • Define platform abstractions across cloud environments — AWS, GCP, Azure, and on-premises • Participate actively in architectural reviews and RFCs; contribute well-reasoned, documented design proposals Control Plane • Build and evolve systems for tenant provisioning, lifecycle management, and configuration • Implement cluster orchestration and management workflows that operate reliably at scale • Develop APIs and automation enabling self-service for operators and tenants • Ensure your areas of ownership are highly available, auditable, and observable Data Plane • Implement data path components for high-throughput, low-latency workloads • Build and enforce isolation boundaries between tenants at the data layer • Optimize for performance, reliability, and cost efficiency within your feature areas Engineering Excellence • Uphold and contribute to technical standards and coding practices for the platform team • Identify and address reliability, scalability, and security risks within your scope • Partner with SRE and DevOps on observability, incident response, and capacity planning Mentorship & Collaboration • Mentor and grow mid-level engineers through code review, design feedback, and pairing • Contribute to hiring as an interviewer; help calibrate the bar for platform engineers • Work closely with cross-geo engineering teams to align on platform direction and delivery What You'll Bring: SaaS Platform & Multi-Tenancy • Hands-on experience building or operating multi-tenant SaaS platforms — silo/pool/bridge models, noisy neighbor mitigation, tenant resource quotas, and lifecycle automation (onboarding, provisioning, offboarding) • Familiarity with data isolation strategies — schema-per-tenant, database-per-tenant, row-level security, and per-tenant encryption at rest Control Plane & Data Plane • Experience with control plane / data plane separation and cluster management — Kubernetes operators, CRDs, admission webhooks, RBAC, and namespace isolation • Working knowledge of configuration management at scale — GitOps workflows, feature flags, and dynamic config propagation across distributed environments Cloud & Infrastructure • Solid hands-on experience with at least one of AWS, GCP, or Azure — VPC, IAM, managed Kubernetes (EKS/GKE/AKS), IaC (Terraform/Pulumi), and cloud cost awareness • Familiarity with service mesh technologies — Istio, Linkerd, or Envoy — for traffic management, mTLS, and microservices observability Distributed Systems & Security • Good understanding of distributed systems fundamentals — HA patterns, fault tolerance, observability (OpenTelemetry, Prometheus, Grafana), and resilience testing • Awareness of zero-trust security, secrets management (Vault, AWS Secrets Manager), and compliance requirements (SOC 2, ISO 27001) at the infrastructure level AI-Augmented Engineering • Actively uses AI coding assistants — Claude, Cursor, Copilot — for infrastructure tasks, runbook generation, and incident analysis • Can craft effective prompts for engineering problems and critically evaluate AI-generated output Good to Have • Exposure to FinOps practices — cost attribution per tenant, showback/chargeback models, and cloud cost anomaly detection • Experience building or contributing to observability platforms — centralized logging pipelines, metrics dashboards (Grafana, Datadog), distributed tracing, and alerting systems • Contributions to open-source infrastructure or platform projects What Success Looks Like In 3 months: • Solid understanding of the current platform architecture, key systems, and near-term roadmap • Shipped at least one meaningful improvement to control or data plane with minimal guidance • Building good working relationships with team members across engineering and product In 6 months: • Owning and delivering a significant platform feature or subsystem end-to-end • Proactively identifying and raising reliability or scalability risks within your area • Actively conducting interviews and contributing to team hiring In 12 months: • Recognized as a strong technical voice on the platform team for your area of ownership • Delivered measurable improvements to platform reliability, scale, or developer experience • Mid-level engineers you've worked with showing clear growth in design and execution quality