Senior/Staff Cloud Reliability Engineer

ThoughtSpot; Mountain View (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

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

Required are 6+ years of SaaS ops, Go/Python proficiency, IaC expertise with Terraform/Ansible, and strong cloud security know-how.

Qualifications

• B.Tech. degree in Computer Science or equivalent.
• 6+ years of Enterprise SaaS Ops experience.
• Strong proficiency in Go and Python; IaC tools like Terraform/Ansible.
• Experience with cloud security and cloud networking.
• Experience with AI Ops tools and Agentic LLMs.

Responsibilities

• Operate a high-scale multi-cloud SaaS platform (AWS, GCP) for reliability and uptime.
• Embed AI/Agentic workflows into SRE practices for anomaly detection and automated triage.
• Drive capacity planning and autoscaling to support SaaS growth.
• Architect and operate Kubernetes controller frameworks and data/control planes.

Skills

Go

Python

Kubernetes

IaC

Cloud security

AI Ops

PostgreSQL

Education

B.Tech. in CS

Tools

Terraform

Ansible

GitOps

LLM/AI Ops tools

Job description

We are seeking a 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.

Responsibilities

• 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

Required skills/qualifications

• 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.