Senior/Staff Cloud Reliability Engineer

Mode Analytics
Mode Analytics

Mountain View, CA, USA

Posted on Aug 25, 2026

Staff Cloud Reliability Engineer

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.