Senior Site Reliability Engineer, SRE

Articul8 AI

full-time

Posted on: 9/7/2025

Location: California • 🇺🇸 United States

✨ AI Apply

Senior

AWSAzureCloudDistributed SystemsDockerGoGoogle Cloud PlatformGrafanaKubernetesNoSQLPrometheusPythonSQLTerraform

About the role

Architect and maintain scalable, highly available infrastructure for our GenAI platform
Design and implement robust monitoring, alerting, and observability solutions to proactively ensure system health and performance
Automate deployment, scaling, and management of our cloud-native infrastructure, reducing toil and improving efficiency
Define, measure, and improve Service Level Objectives (SLOs) and Service Level Indicators (SLIs)
Participate in on-call rotations and provide rapid response to production incidents
Collaborate closely with development teams to build reliable, scalable, and efficient systems for complex AI workloads
Lead incident response efforts, conduct thorough post-mortems, and champion continuous improvement initiatives
Optimize infrastructure for performance, scalability, and cost-effectiveness—especially for high-demand AI workloads
Implement and enforce security best practices across all systems and environments
Create and maintain comprehensive documentation, including runbooks and knowledge base articles

Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience
5+ years of experience in DevOps, SRE, or similar roles
Strong experience with cloud platforms (AWS, GCP, or Azure)
Proficiency in at least one programming/scripting language (Python, Go, Bash, etc.)
Hands-on experience with infrastructure as code tools (Terraform, CloudFormation, etc.)
Solid background in containerization technologies (Docker, Kubernetes)
Proven experience with monitoring and observability tools (Prometheus, Grafana, ELK stack, etc.)
Strong understanding of CI/CD pipelines and automation
Exceptional troubleshooting and problem-solving skills and ability to troubleshoot complex systems
Experience supporting AI/ML systems in production (preferred)
Knowledge of GPU infrastructure management and optimization (preferred)
Familiarity with distributed systems and high-performance computing (preferred)
Experience with database systems (SQL and NoSQL) (preferred)
Certifications in cloud platforms (AWS, GCP, Azure) (preferred)
Experience with chaos engineering and resilience testing (preferred)
Knowledge of security best practices and compliance requirements (preferred)