Senior Cloud Reliability Engineer

ThoughtSpot; Thiruvananthapuram; On-site; INR 2,800,000 - 4,600,000; Full time

Job summary

ThoughtSpot seeks a Senior Cloud Reliability Engineer to own availability and security for a large multi-cloud SaaS platform. You will drive autonomy via AI Ops, manage Kubernetes-based control and data planes, and optimize capacity with automated scaling.

You will lead incident response, perform root cause analysis, and push for automation-first improvements in a cloud-native environment with PostgreSQL, DynamoDB, and Elasticsearch stacks.

Qualifications

• Requires a B.Tech. in Computer Science or equivalent.
• 6+ years of Enterprise SaaS Operations experience.
• Strong programming skills in Go and Python, plus IaC tooling (Terraform, Ansible).

Responsibilities

• Operate a high-scale multi-cloud SaaS platform (AWS, GCP) ensuring reliability and uptime.
• Embed AI Ops and autonomous agents to improve anomaly detection and MTTR.
• Drive capacity planning and automated scaling to support growth.
• Architect and operate Kubernetes controller frameworks for control/data planes.
• Manage cloud-native databases and data infrastructure with performance tuning and backups.
• Lead incident response and blameless post-mortems for critical events.
• Promote automation-first culture with IaC and GitOps pipelines.
• Participate in on-call rotations and act as escalation point.

Skills

Go

Python

AI Ops

LLM

Cloud security

Cloud networking

Kubernetes

Observability

Microservices

PostgreSQL

Education

B.Tech. degree in Computer Science or equivalent

Tools

Terraform

Ansible

Kubernetes

PostgreSQL

MySQL

DynamoDB

Elasticsearch/OpenSearch

ElastiCache (Redis/Memcached)

Job description

We are seeking a Senior Cloud 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.