Staff Engineer - Developer Platforms

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