Job description

What You'll Do: Technical & Customer Support • Act as the primary point of contact for customer-facing technical issues related to our SaaS platform, including data connectivity, report errors, performance concerns, access problems, data inconsistencies, software bugs, and integration challenges. • Understand and empathize with the challenges ThoughtSpot users face, offering tailored solutions to improve their experience. • Provide timely, accurate, and clear updates to customers, consistently meeting SLAs and driving issues through to full resolution via tickets and calls. • Translate complex technical issues into clear, concise updates for both technical and non-technical stakeholders. • Create and maintain knowledge-base articles to empower customer self-service and improve support efficiency. System Reliability & Monitoring • Maintain, monitor, and troubleshoot ThoughtSpot cloud infrastructure using tools like Grafana, Prometheus, Datadog, and Splunk. • Monitor system health and performance through metrics, logs, and dashboards to detect and prevent issues proactively. • Implement and leverage AI/ML-driven solutions for proactive observability, predictive anomaly detection, and intelligent alerting to enhance service reliability and reduce Mean Time to Resolution (MTTR). • Understand and apply NetOps and SecOps principles for cloud and on-premise deployments. • Develop and implement automation and best practices to streamline operations and strengthen system reliability. • Optimize SRE workflows with AI tools to boost operational effectiveness. Incident Management & Continuous Improvement • Participate in on-call rotations, lead incident reviews, and conduct thorough root cause analyses to drive continuous improvement. • Work cross-functionally with Engineering to define and implement tools that enhance debuggability, supportability, availability, scalability, and performance. • Be an expert in both cloud and on-premise infrastructure by developing automation and best practices. What You'll Bring • B.S. in Computer Science or equivalent relevant experience. • Proven experience troubleshooting complex Linux systems and managing virtualization and cloud platforms (VMware, AWS, Azure, GCP). • Hands-on experience with monitoring tools such as Grafana, Prometheus, Datadog, or Splunk. • Demonstrated experience and a keen interest in leveraging AI/ML principles to address SRE challenges — including AIOps, predictive maintenance, and intelligent automation. • Prior experience in enterprise customer support, including on-call rotations and incident management, with the ability to lead root cause analyses. • Strong problem-solving and algorithmic thinking with a solid understanding of system internals. • Excellent verbal and written communication skills with the ability to work independently and cross-functionally in fast-paced environments. • Familiarity with scripting and programming languages such as Python, Go, Bash, or Java. • Exposure to infrastructure and service monitoring frameworks with the ability to analyze data to ensure high availability. Good to Have • Experience partnering with Engineering to design and implement mission-critical tooling and automation that advances system debuggability, high availability, elastic scalability, and performance. • Experience with alerting strategies and monitoring system tuning to minimize alert fatigue and optimize Mean Time to Acknowledge (MTTA). • Familiarity with C/C++ or other low-level systems languages. Ideal Candidate Profile: You have a balanced mix of technical expertise in cloud operations and a proven record of handling support incidents and end-user queries. This sets you apart from candidates with purely systems or cloud engineering backgrounds. You move fluidly between deep technical investigation and customer-facing communication — equally at home diagnosing a complex infrastructure issue and presenting findings clearly to an enterprise stakeholder. What We Offer • Competitive salary and benefits package. • Opportunities for professional growth and career advancement. • A collaborative work environment where your input and expertise directly impact customer experience and platform reliability. In-Office at ThoughtSpot Spotters are expected in-office 3+ days per week to be part of the energy of their local team. Momentum compounds when we're in the room together with faster decisions, sharper problem-solving, and the kind of peer learning that doesn't happen over a screen. Being in-office is our default way of working, with flexibility available where it's genuinely needed. 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. 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. 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. The Role: As part of the ThoughtSpot SRE team, you will be on the cutting edge of operational intelligence. You will not only ensure service reliability but also act as a trusted partner for our customers — proactively leveraging AI/ML to deliver timely updates, meaningful solutions, and predictive improvements. You are the bridge between our customers and engineering, combining deep systems expertise with a genuine passion for customer success. If you thrive in dynamic environments and are committed to building resilient, self-optimizing systems, this role is for you.

Requirements

Must-haves

Technical & Customer Support
Understand and empathize with the challenges ThoughtSpot users face, offering tailored solutions to improve their experience.
Provide timely, accurate, and clear updates to customers, consistently meeting SLAs and driving issues through to full resolution via tickets and calls.
Translate complex technical issues into clear, concise updates for both technical and non-technical stakeholders.
Create and maintain knowledge-base articles to empower customer self-service and improve support efficiency.
System Reliability & Monitoring
Maintain, monitor, and troubleshoot ThoughtSpot cloud infrastructure using tools like Grafana, Prometheus, Datadog, and Splunk.
Monitor system health and performance through metrics, logs, and dashboards to detect and prevent issues proactively.
Implement and leverage AI/ML-driven solutions for proactive observability, predictive anomaly detection, and intelligent alerting to enhance service reliability and reduce Mean Time to Resolution (MTTR).
Understand and apply NetOps and SecOps principles for cloud and on-premise deployments.
Develop and implement automation and best practices to streamline operations and strengthen system reliability.
Optimize SRE workflows with AI tools to boost operational effectiveness.
Incident Management & Continuous Improvement
Participate in on-call rotations, lead incident reviews, and conduct thorough root cause analyses to drive continuous improvement.
Work cross-functionally with Engineering to define and implement tools that enhance debuggability, supportability, availability, scalability, and performance.
Be an expert in both cloud and on-premise infrastructure by developing automation and best practices.
B.S. in Computer Science or equivalent relevant experience.
Proven experience troubleshooting complex Linux systems and managing virtualization and cloud platforms (VMware, AWS, Azure, GCP).
Hands-on experience with monitoring tools such as Grafana, Prometheus, Datadog, or Splunk.
Demonstrated experience and a keen interest in leveraging AI/ML principles to address SRE challenges — including AIOps, predictive maintenance, and intelligent automation.
Prior experience in enterprise customer support, including on-call rotations and incident management, with the ability to lead root cause analyses.
Strong problem-solving and algorithmic thinking with a solid understanding of system internals.
Excellent verbal and written communication skills with the ability to work independently and cross-functionally in fast-paced environments.
Familiarity with scripting and programming languages such as Python, Go, Bash, or Java.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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