Platform Engineering - Staff Engineer

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

Must Have

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