Senior SRE partners with a product team to architect reliable systems, define SLOs/SLIs, eliminate toil via automation, and build shared platform tooling on AWS. Requires 6+ years experience with Terraform, Datadog, container orchestration, Python/Bash, and AI familiarity.
Salary not listed
Hybrid6+ YOEDevOps / SRE
About the role
Responsibilities
Reliability Architecture for Your Product Team
Engage early in architecture reviews and design discussions to surface risks
Lead Production Readiness Reviews (PRRs) before new services launch
Partner with product engineering leads to define SLOs and SLIs for critical services
Participate in team planning and architecture reviews
Identify repeated manual work and convert to self-service tooling or runbooks
Audit existing services for reliability anti-patterns
Central SRE Platform Work
Design and build shared platform infrastructure: reusable Terraform modules, standardized observability stacks, service templates
Participate in on-call rotation, lead incident response, conduct post-incident reviews
Design and manage CI/CD pipelines using GitHub Actions
Contribute to evolving SRE standards, tooling, and practices
Requirements
6+ years of experience in Site Reliability Engineering, Cloud Engineering, or building scalable services
Robust knowledge of Terraform, Docker, Git, Linux
Hands-on experience with Datadog for monitoring, alerting, dashboards, SLO tracking, distributed tracing
Experience building software systems as a software engineer
Experience developing tooling and automation in Python and/or Bash
Experience with CI/CD pipeline automation, specifically GitHub Actions
Experience with disaster recovery practices and incident management
Strong understanding of observability concepts (monitoring, logging, distributed tracing, metrics)
Experience with container orchestration: AWS ECS Fargate and/or Kubernetes
Experience with relational databases (MySQL proficiency a plus)
Ability to take ownership independently
AI Experience (at least one): AI-assisted development tools (GitHub Copilot, etc.), AI/AIOps for reliability, operational characteristics of AI/ML services, or passion for AI in infrastructure
Nice to Have
Experience with AIOps (AI/ML for anomaly detection, predictive alerting, incident triage)
Familiarity with reliability of AI/ML-backed services (LLM inference, non-determinism)
Experience with JavaScript/Node.js ecosystem
Certified Kubernetes Administrator (CKA)
Familiarity with compliance frameworks (SOC 2, ISO 27001, NIST)
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