• Following SRE principles to maintain a 24/7 production environment running on Kubernetes • Implementation of DevOps methodologies to improve IT team quality of life • Proactive system monitoring and configuration • Incident response and postmortem processes • Managing and evolving AWS infrastructure (EKS, EC2, RDS, Fargate, CloudFront, Lambda, S3) • Building and maintaining CI/CD pipelines, infrastructure as code (Terraform, Helm, ArgoCD) • Ensuring system reliability, performance, and scalability across our production stack • Applying SRE discipline to ML infrastructure — ensuring model serving, training pipelines, and data systems are reliable, observable, and well-operated • Supporting and improving ML model deployment pipelines and MLOps practices • Monitoring ML model performance in production and building alerting and observability for ML systems • Collaborating with data scientists and product teams to operationalize ML models at scale • Contributing to infrastructure for ML workloads on Kubernetes and AWS

Title: Site Reliability Engineer Location: Chandler, AZ Duration: 12 months Work Engagement: W2 Work Schedule: Hybrid 3 days in office/2 days remote Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits Summary: In this contingent resource assignment, you may: Participate in low to moderately complex initiatives and identify opportunity for process improvements within Systems Operations Engineering. Review and analyze basic or tactical Systems Operations Engineering assignments or challenges that require research, evaluation, and selection of alternatives, related to low-to-medium risk deliverables. Present recommendations for resolving low to moderately complex situations and exercise some independent judgment while developing understanding of function, policies, procedures, and compliance requirements. Provide information to client personnel in Systems Operations Engineering. Required Qualifications: Systems Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education. Key Requirements: · Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship. Technical Skills • Experience supporting production applications or infrastructure. • ServiceNow or similar ITSM platform experience. • Experience working with monitoring and observability tooling. • Unix/Linux and Windows fundamentals. • Experience troubleshooting application and batch processing issues. • Understanding of change, incident, and problem management processes. Automation Skills • Basic coding or scripting knowledge in one or more of: o PowerShell o Python o Shell scripting o Low-code automation platforms • Ability to modify, validate, and execute automation workflows. • Willingness to continue developing automation and AI skills. Reliability Engineering Fundamentals • Basic understanding of monitoring and alert management. • Analytical approach to troubleshooting and problem solving. • Understanding of operational risk and production support practices. • Interest in reliability engineering and continuous improvement.

• Enhance cloud infrastructure and ensure reliability of applications through automation and best practices • Work closely with development teams to implement CI/CD pipelines • Manage cloud resources and optimize system performance

• Design, build, and scale Kubernetes infrastructure for secure, multi-tenant, high-availability applications. • Build and operate AI tooling infrastructure — stand up MCP servers and establish secure, governed AI access and guardrails for production systems. • Optimize and maintain CI/CD pipelines, improving reliability, speed, and rollback safety. • Implement progressive delivery strategies such as blue/green and canary deployments. • Advance Infrastructure as Code with Terraform, Helm, and Argo CD, defining reusable patterns for the org. • Operate and optimize streaming and analytics infrastructure: Kafka, Flink, and ClickHouse. • Build automated testing into the CI/CD lifecycle. • Improve system observability — define SLOs, alerts, and dashboards. • Lead incident response and postmortems, focusing on root cause and durable fixes. • Mentor engineers across teams on Kubernetes, CI/CD, and cloud infrastructure.