Sr Site Reliability Engineer

Job Description

On behalf of our Technology client, Procom is searching for a Sr Site Reliability Engineer for a 6 month contract. This position is a hybrid position with 4 days onsite at our client’s Austin, TX office.

Sr Site Reliability Engineer - Job Description:
We are seeking a skilled Sr Site Reliability Engineer to enhance our software systems engineering and operations with AI/ML-driven approaches. The focus is on improving application observability and reliability through innovative solutions and automation.

Sr Site Reliability Engineer - Responsibilities:
• Evangelize SRE mindset and solve problems through systematization.
• Identify opportunities to build innovative tools and solve unique operations problems on large enterprise and mission-critical applications.
• Create scripts to automate operational tasks and incorporate solutions into infrastructure.
• Design and implement AI/ML-driven automation pipelines and observability enhancements.
• Lead expansion of automation coverage across deployment, monitoring, alerting, and self-healing workflows.
• Collaborate with Engineering, Scrum, and Ops resources to provide technical expertise and support.
• Triage alerts, diagnose/resolve critical issues, and manage implementation of changes.

Sr Site Reliability Engineer - Mandatory Skills:
• 6-8 years of experience with enterprise-level administration and support.
• Experience writing automation scripts and building application dashboards.
• Hands-on enterprise systems administration, monitoring, and deployment activities.
• Experience with Windows 2019/2022 and Linux hosted via Virtual Machine.
• Development experience in one or more programming languages: .NET, PowerShell, Java, Python, Bash.
• Knowledge of one or more Message Brokers: Solace, RabbitMQ, IBM MQ, Kafka.
• Demonstrated experience applying AI/ML or AIOps approaches in production environments.

Sr Site Reliability Engineer – Nice-to-Have Skills:
• Financial services industry experience.
• Agile methodologies.
• Hands-on experience with AIOps platforms or ML-driven observability tooling.
• Familiarity with CI/CD tools or GitOps concepts.
• Exposure to container orchestration or cloud platforms.