Senior Cloud Reliability Engineer

ThoughtSpot; Bengaluru; On-site; INR 3,500,000 - 6,000,000; Full time

Benefits offered by this job

In-office in Bengaluru (3+ days/wk)

Job summary

ThoughtSpot is seeking a Senior/Staff Site Reliability Engineer to own the availability, reliability, and security of our multi-cloud SaaS platform (AWS, GCP). You will drive automation, AI-augmented operations, and incident response for a large Kubernetes-based data platform.

The role requires 6+ years in Enterprise SaaS operations, strong Go/Python skills, and IaC experience; in-office presence in Bengaluru is expected.

Qualifications

• B.Tech. degree in Computer Science or equivalent.
• At least 6+ years of Enterprise SaaS Ops experience.
• Strong programming skills in Go and Python; IaC experience with Terraform and Ansible.
• Expertise in Cloud security and networking.
• Experience with AI Ops tools and Agentic LLMs.
• Knowledge of cloud services, Kubernetes, and cloud databases.
• Experience with observability stacks (metrics, logs, tracing) in SaaS.
• Certifications from AWS/Azure/GCP are a bonus.

Responsibilities

• Operate a high-scale multi-cloud SaaS platform (AWS/GCP) ensuring reliability and uptime.
• Integrate AI Ops, LLM-powered agents for anomaly detection and automated triage.
• Drive capacity planning and autoscaling to support SaaS growth.
• Architect and run Kubernetes controller frameworks with proper standards.
• Manage cloud-native databases and data infrastructure including backups and recovery.
• Lead incident response and post-mortems to permanent resolutions.
• Champion automation-first culture with IaC, GitOps, and self-healing systems.
• Participate in on-call rotations and act as senior escalation point.

Skills

Go

Python

Terraform

Ansible

Kubernetes

Cloud (AWS/GCP)

PostgreSQL/RDS

Elasticsearch/OpenSearch

Observability

GitOps

AI Ops / LLM

Education

B.Tech. in Computer Science or equivalent

Tools

Terraform

Helm

Docker

Job description

ThoughtSpot is a Data & AI platform that helps companies turn data into enterprise advantage. We're Gartner MQ leaders with more than 1,000 customers globally and offices in Mountain View, Chicago, London, Bangalore, Sydney, and Tokyo.

The Role:

We are seeking a Senior/Staff Site Reliability Engineer with deep enterprise SaaS operations expertise to own the availability, reliability, security, and efficiency of our Multi-Cloud (AWS, GCP) production SaaS platform. The ideal candidate brings hands-on experience running highly available, large-scale Kubernetes-based control and data planes, a strong bias toward automation and AI-augmented operations, and a proven track record in production security, capacity management, and cloud-native data infrastructure.

What You'll Do:

• Operate a high-scale, multi-cloud (AWS, GCP) SaaS platform — ensuring reliability, performance, and uptime for business-critical production workloads.
• Embed AI and Agentic workflows into SRE practice: leverage AI Ops platforms and LLM-powered autonomous agents for anomaly detection, automated triage, runbook execution, and incident summarization to reduce MTTR.
• Drive capacity planning and scaling operations — proactively model growth, right-size infrastructure, and implement horizontal/vertical autoscaling strategies to support SaaS growth without reliability regression.
• Architect and operate Kubernetes controller frameworks governing both control plane and data plane services; define and enforce operational standards for cluster lifecycle, workload scheduling, autoscaling, and failover.
• Own operations of high-scale cloud-native databases and data infrastructure: PostgreSQL/RDS, DynamoDB, MySQL, Elasticsearch/OpenSearch, ElastiCache (Redis/Memcached) on AWS and GCP — including performance tuning, backup/recovery, and incident response.
• Lead incident response and blameless post-mortems for P0/P1 events; drive root cause analysis to permanent resolution and prevention — eliminating repeat incidents through systemic fixes, not workarounds.
• Define and enforce a culture of automation-first: identify and eliminate toil through self-healing systems, automated remediation pipelines, and infrastructure-as-code (Terraform, Helm, GitOps).
• Participate in on-call rotations for critical cloud infrastructure; serve as a senior escalation point and incident commander during high-severity events.
• Achieve quantifiable SaaS operational Excellence measured by related SLI/SLO/SLA

What You Bring:

• B.Tech. degree in Computer Science or equivalent.
• At least 6+ years of Enterprise SaaS Ops experience
• Strong proficiency in programming, particularly with Go and Python, and experience with Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Expertise in Cloud Security and/or Cloud networking
• Experience with AI Ops tools, Agentic LLM.
• Experience/ Knowledge in Cloud Services, Kubernetes, Cloud Databases like Postgres/RDS/MySQL/DynamoDB, Elastic, Kafka, and Microservice architecture is a bonus.
• Experience in implementing and operating enterprise-grade observability ( metrics, logs, tracing), alerting stack in a Cloud SaaS environment
• Strong debugging and problem-solving skills (network, systems, database, and application).
• Advanced professional certifications from Cloud Providers ( AWS, Azure, GCP) in domains like K8s, Solution architecture, networking, and databases are a bonus.
• Full Stack Architecture/Development Experience is a bonus.

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