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 at scale. This 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. What You Will Do Architecture & Design 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 Control Plane 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 Data Plane Design data path components for high‑throughput, low‑latency workloads Build and enforce isolation boundaries between tenants at the data layer Optimise for performance, reliability, and cost efficiency at scale Engineering Excellence Set technical direction and coding standards for the platform team Identify and address systemic risks—reliability, scalability, security, and operability Partner with SRE and DevOps on observability, incident response, and capacity planning Must Have SaaS Platform & Multi‑Tenancy Hands‑on experience building or operating multi‑tenant SaaS platforms at scale: 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 Control Plane & Data Plane Proven experience with control plane / data plane separation and cluster management—including Kubernetes operators, CRDs, admission web‑hooks, RBAC, and namespace isolation Understanding of configuration management at scale—including GitOps workflows, feature flags, and dynamic config propagation across distributed environments Cloud & Hybrid Infrastructure 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 Distributed Systems & Security Strong grasp of distributed systems fundamentals: HA patterns, fault tolerance, observability (OpenTelemetry, Prometheus, Grafana), and resilience testing Understanding of zero‑trust security, secrets management (Vault, AWS Secrets Manager) AI-Augmented Engineering Actively uses AI coding assistants—Claude, Cursor, Copilot—for infrastructure tasks, runbook generation, incident analysis, and ADR drafting Able to craft effective prompts for complex engineering problems and critically evaluate AI output; evaluates and drives AI tool adoption across the platform team Good to Have Exposure to FinOps 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 Compensation & Benefits In California, the estimated annual salary range for this role is $100K – $120K 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 for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits. Mandatory and Required Skills for All ThoughtSpot Roles Spotters are expected to demonstrate AI literacy and workflow integration, including the ability to: Comfortably and confidently integrate artificial intelligence into their daily workflow to increase productivity and quality. Hands‑on experience to leverage AI tools (industry‑leading LLMs) to increase productivity, automate routine tasks, and improve work quality. Speak to the experience of using AI for research, content creation, and document summarisation while maintaining ownership of judgment and final decisions. Write effective prompts to get the most accurate and creative results from AI tools. Spotters are expected to exemplify these key traits and AI mindset: 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 AI Mindset for All Spotters At ThoughtSpot, we believe AI is a necessary and essential part of how we work. Every role, across every team, is expected to be fluent and comfortable with using AI to do their best work. All Spotters are expected to experiment with ThoughtSpot’s AI tools (like Spotter and SpotterViz) to streamline workflows, enhance output, and uncover new insights. Whether drafting content, analysing data, or summarising documents, AI is a daily partner. We value curiosity, openness to learning, and thoughtful application of AI to create real value. Training and resources are provided so every Spotter can confidently create with AI. Hybrid Work at ThoughtSpot This office‑assigned role is available as a hybrid position, reporting to the office in US – Mountain View. Spotters assigned to an office are encouraged to experience the energy of their local office with an in‑office expectation of 2‑3 days per week. This approach balances the benefits of in‑person collaboration and peer learning with the flexibility needed by individuals and teams. #J-18808-Ljbffr Cerebras