About the Role:

We are looking for a Senior Engineer to join our Cloud Platform team and contribute to the development, operation, and reliability of our multi-tenant SaaS platform. You will work on backend systems and

Cloud infrastructure — building features, fixing real production problems, and growing into broader ownership over time.

This is a hands-on role with real ownership. You are expected to take a feature or problem end-to-end, write production-quality code, and work closely with more senior engineers on design and architecture.

What You Will Do:

Engineering & Development

• Build and maintain platform components across control plane and data plane

• Implement features for tenant provisioning, configuration management, and cluster operations

• Write clean, well-tested, production-grade code and participate actively in code reviews

• Debug and resolve issues in cloud-native, distributed production environments

Operations & Reliability

• Partner with SRE on observability, alerting, and incident response for services you own

• Improve reliability and operability of platform systems — reduce toil, improve monitoring, fix recurring issues

• Contribute to on-call and develop strong instincts for production system behaviour.
  

Collaboration & Growth

• Work closely with senior and principal engineers on design discussions and RFCs

• Collaborate with cross-functional teams across geographies

• Participate in hiring — conduct interviews and contribute feedback.
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Must Have:

Cloud & Infrastructure

• Solid hands-on experience with at least one of AWS, GCP, or Azure — compute, networking, IAM, and managed services

• Working knowledge of infrastructure as code — Terraform or equivalent — for provisioning and managing cloud resources.

• Comfortable working with containerized workloads — Docker, Kubernetes basics (deployments, services, config maps, RBAC, namespaces)
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Backend Engineering

• Strong programming skills in at least one backend language — Go, Java, Python, or equivalent

• Experience building and operating REST or gRPC APIs in production

• Good understanding of databases — relational and NoSQL — and how to use them reliably at scale

Distributed Systems

• Practical understanding of distributed systems — service dependencies, failure modes, retries, timeouts, and basic HA patterns.

• Hands-on with observability — structured logging, metrics dashboards (Grafana, Datadog, or equivalent), and basic alerting; able to diagnose production issues using these tools

Security Fundamentals

• Awareness of cloud security basics — IAM least-privilege, secrets management, and network access controls

AI-Augmented Engineering

• Uses AI coding assistants — Claude, Cursor, Copilot — as a regular part of daily workflow for writing, debugging, and reviewing code

• Comfortable using AI tools to understand unfamiliar codebases, generate boilerplate, draft documentation, and speed up routine tasks

• Knows to review AI output carefully and apply judgment before committing or deploying

Good to Have

• Exposure to Kubernetes operators, controllers, or CRDsFamiliarity with GitOps workflows — ArgoCD, Flux, or equivalent

• Basic understanding of multi-tenancy concepts — isolation, resource quotas, or tenant lifecycleExperience contributing to or building internal observability dashboards and alerting pipelines.

What Success Looks Like

In 3 months:

- Ramped up, productive, and shipping features with guidance

- Comfortable with the codebase, deployment process, and team workflow

- Engaging actively in code reviews and team discussions

In 6 months:

- Owning features end-to-end with increasing independence

- Reliable on-call contributor — able to diagnose and resolve common production issues

- Proactively improving the quality and observability of systems you work on

In 12 months:

- Trusted, high-output contributor on the team

- Beginning to mentor interns or junior engineers

- Taking on broader problems that span multiple components or systems

Mandatory and Required Skills for All ThoughtSpot Roles

Spotters are expected to demonstrate AI literacy and workflow integration to include to 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 summarization 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

This combination of curiosity, adaptability, and discernment defines the AI mindset, and it’s required for every role at ThoughtSpot.

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) and leading industry LLMs to streamline workflows, enhance output, and uncover new insights. Whether drafting content, analyzing data, or summarizing 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 India - Bangalore.

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.

ThoughtSpot for All

At ThoughtSpot, diverse teams build better products. Complex data problems need many perspectives, not just one. We welcome different backgrounds, identities, and experiences, and we work to create a place where everyone can be themselves and do their best work. If this role excites you and you believe you’re a strong match, we encourage you to apply.

What Makes ThoughtSpot a Great Place to Work?

ThoughtSpot is the Agentic Analytics Platform that empowers every enterprise to transform insights into action, on a mission to make the world more fact driven. We hire people with unique identities, backgrounds, and perspectives - this balance-for-the-better philosophy is key to our success. When paired with our culture of Trust, Customer Obsession, Innovation and Intensity, ThoughtSpot cultivates a respectful culture that pushes norms to create world-class products. If you’re excited by the opportunity to work with some of the brightest minds in the business and make your mark on a truly innovative company, we invite you to read more about our mission, and apply to the role that’s right for you.

About ThoughtSpot

The world’s most innovative companies turn to ThoughtSpot’s AI-Powered Analytics to put data in the hands of everyone, from the C-suite to the frontline. With simple, natural language search and AI, anyone can ask questions, discover insights, and act with confidence. Unlike legacy tools that sacrifice performance for complexity, ThoughtSpot is intuitively designed for every business user while being built to handle the most complex, large-scale data, wherever it resides. This unique combination of speed and simplicity is why enterprise leaders trust ThoughtSpot to transform decision-making into a truly data-driven culture.

At ThoughtSpot, we’re a curious, data-driven bunch. We believe the world works better when everyone has access to facts. That’s why we build products that make asking and answering data questions as natural as having a conversation.