Senior Member of Technical Staff

About the Role

We are looking for a Senior Engineer to join our Cloud Platform team and take ownership of the architecture and evolution of our multi‑tenant SaaS platform. You will work at the intersection of backend engineering and cloud infrastructure, designing and building the systems that power our control plane and data plane s is a high‑impact, high‑ownership role. You will be a technical anchor for the team, driving architecture decisions, mentoring engineers, and partnering with product and infrastructure leaders to shape the future of our cloud platform.

• Own end‑to‑end architecture for the cloud platform, spanning control plane and data plane
• Design multi‑tenant systems with strong isolation, security, and resource governance
• Define platform abstractions that work across hybrid environments AWS, GCP, Azure, and on‑premises
• Drive architectural reviews, RFCs, and ensure decisions are well‑reasoned, documented, and scalable

• Architect and build systems for tenant provisioning, lifecycle management, and configuration
• Design cluster orchestration and management systems that operate reliably at scale
• Build APIs and automation that enable self‑service for operators and tenants
• Ensure control plane is highly available, auditable, and observable

• Design 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 at scale

• Set technical direction and coding standards for the platform team
• Identify and address systemic risks — reliability, scalability, security, and operability
• Partner with SRE and Dev Ops on observability, incident response, and capacity planning

• Hands‑on experience building or operating multi‑tenant SaaS platforms at scale with silo/pool/bridge models, noisy neighbour mitigation, tenant resource quotas, and lifecycle automation (onboarding, provisioning, off‑boarding)
• Knowledge of data isolation strategies: schema‑per‑tenant, database‑per‑tenant, row‑level security, and per‑tenant encryption at rest
• Proven experience with control plane/data plane separation and cluster management — Kubernetes operators, CRDs, admission web‑hooks, RBAC, and namespace isolation
• Understanding of configuration management at scale — Git Ops workflows, feature flags, and dynamic config propagation across distributed environments
• Deep expertise in any one of AWS, GCP, or Azure: VPC, IAM, managed Kubernetes (EKS/GKE/AKS), IaC (Terraform/Pulumi), and cost optimisation across hybrid environments
• Familiarity with service mesh technologies — Istio, Linkerd, or Envoy for traffic management, mTLS, and microservices observability
• Strong grasp of distributed systems fundamentals: HA patterns, fault tolerance, observability (Open Telemetry, Prometheus, Grafana), and resilience testing
• Understanding of zero‑trust security, secrets management (Vault, AWS Secrets Manager)
• Actively uses AI coding assistants — Claude, Cursor, Copilot — for infrastructure tasks, runbook generation, incident analysis, and ADR drafting; abilable to craft effective prompts for complex engineering problems and critically evaluate AI output; evaluates and drives AI tool adoption across the platform team

• Exposure to Fin Ops practices
• Hands‑on experience building and maintaining observability platforms, centralised logging pipelines, metrics dashboards (Grafana, Datadog, or equivalent), distributed tracing infrastructure, and alert management systems that give engineering teams real‑time visibility into platform health
• Contributions to open‑source infrastructure or platform projects

• In California, the estimated annual salary range for this role is $175K – $220K per year. Actual compensation may vary and will be determined based on permissible, non‑discriminatory factors such as skills, qualifications, experience, and location of the selected candidate.
• Additional benefits may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits.

• Comfortably and confidently integrate artificial intelligence into their daily workflow to increase productivity and quality.
• Hands‑on experience leveraging AI tools (industry‑leading LLMs) to increase productivity, automate routine tasks, and improve work quality.
• Write effective prompts to get the most accurate and creative results from AI tools.
• Curiosity in exploring new AI tools.
• Adaptability to quickly learn and implement new, emerging AI technologies.
• Critical thinking to know when to identify when AI should be used versus when human judgement is necessary.

• Enable in‑office presence 3 days per week.