Senior Member Of Technical Staff- Platform Engineering
ThoughtSpot
Job Description
About the Role
We are looking for a Senior Engineer to join our Cloud Platform Engineering team and contribute to building and operating a multi-tenant SaaS platform at scale.
This is a hands-on engineering role where you will work across backend systems and cloud infrastructure—building features, solving real production problems, and gradually expanding your ownership.
You will take problems end-to-end, write production-quality code, and collaborate closely with senior engineers on design and architecture.
What You’ll Do
Build & Ship
- Develop and maintain platform components across control plane and data plane
- Build features for tenant provisioning, configuration management, and cluster operations
- Write clean, well-tested, production-grade code and actively participate in code reviews
- Debug and resolve issues in cloud-native, distributed systems
Operate & Improve
- Partner with SRE on observability, alerting, and incident response
- Improve system reliability, scalability, and operability
- Contribute to on-call rotations and build strong production instincts
Collaborate & Grow
- Work with senior engineers on design discussions and RFCs
- Collaborate with cross-functional and global teams
- Participate in hiring and contribute to maintaining a strong engineering bar.
What You’ll Have
Cloud & Infrastructure
- Hands-on experience with AWS, GCP, or Azure (compute, networking, IAM, managed services)
- Experience with Infrastructure as Code (Terraform or equivalent)
- Familiarity with containers and Kubernetes basics (deployments, services, RBAC, namespaces)
Backend Engineering
- Strong programming skills in Go, Java, Python, or similar
- Experience building REST or gRPC APIs in production
- Solid understanding of databases (SQL/NoSQL) and their use at scale
Distributed Systems
- Practical understanding of distributed systems fundamentals (failures, retries, timeouts, HA patterns)
- Experience with observability tools (logs, metrics, dashboards, alerting) and debugging production issues
Security Fundamentals
- Awareness of IAM, secrets management, and network security basics
AI-Augmented Engineering
- Regular user of tools like Copilot, Cursor, Claude for coding and debugging
- Able to leverage AI effectively while applying strong engineering judgment
Good to Have
- Exposure to Kubernetes operators, controllers, or CRDs
- Familiarity with GitOps tools (ArgoCD, Flux)
- Understanding of multi-tenancy concepts (isolation, quotas, lifecycle)
- Experience with observability platforms (dashboards, logging, alerting pipelines)
What Success Looks Like
In 3 months:
- Productive and shipping features with guidance
- Comfortable with codebase, systems, and workflows
In 6 months:
- Owning features end-to-end
- Confident in handling production issues and on-call responsibilities
In 12 months:
- Strong, reliable contributor
- Mentoring junior engineers and taking on broader system-level problems