Senior Site Reliability Engineer

TAG - The Aspen Group•Chicago, IL

About The Position

The Aspen Group (TAG) is one of the largest and most trusted retail healthcare business support organizations in the U.S., supporting over 20,000 healthcare professionals and team members across nearly 1,500 health and wellness offices in 48 states. They operate in dental care, urgent care, medical aesthetics, and animal health, partnering with independent practice owners and clinicians to improve healthcare. TAG provides centralized business support services to five consumer-facing businesses: Aspen Dental, ClearChoice Dental Implant Centers, WellNow Urgent Care, Chapter Aesthetic Studio, and Lovet Pet Health Care. As a Senior Site Reliability Engineer (SRE) at TAG, you will be responsible for ensuring the reliability, performance, and scalability of core systems. This role involves proactively building and managing monitoring solutions, leading incident response, and continuously optimizing system performance to exceed business objectives. The position actively integrates AI and machine learning into operational workflows, leveraging intelligent automation and machine learning to build a proactive, resilient infrastructure, offering an opportunity to apply cutting-edge technology to complex reliability challenges.

Requirements

Bachelor's degree in computer science or a related technical field.
At least 5 years of experience in Site Reliability Engineering or a similar role.
Strong proficiency in at least one programming language such as Python, Go, or C#
Demonstrated experience applying machine learning and automation to operational workflows such as monitoring, alerting and incident response.
Expertise with infrastructure as code tools such as Terraform
Proven experience working and monitoring container environments such as Cloud Run and Kubernetes.
Hands-on experience using and working within an Azure, AWS, and GCP environment (GCP preferred)
Strong understanding of networking, distributed systems, and cloud infrastructure.
Familiarity with intelligent monitoring platforms and operational analytics tools such as Prometheus, Grafana, OpenSearch, Sentry, Google Cloud Observability
Excellent problem-solving skills and the ability to work independently and as part of a team.
Experience with incident management, root cause analysis, and automated operational workflows.

Responsibilities

Design and build highly scalable and resilient systems to support our applications and services, incorporating predictive analytics to anticipate reliability risks.
Develop and manage Service Level Objectives (SLOs) and Service Level Indicators (SLIs) using machine learning anomaly detection to ensure systems meet reliability targets.
Drive improvements in system reliability, availability, and performance through proactive measures, automation, and intelligent failure prediction.
Implement and manage comprehensive monitoring and alerting solutions, integrating with intelligent observability platforms that reduce alert noise and correlate events.
Develop and maintain dashboards and reporting tools that provide data-driven insights for actionable troubleshooting recommendations and performance optimization.
Evaluate and integrate advanced monitoring tools and operational intelligence platforms to enhance observability and root cause identification.
Lead and participate in incident response efforts, using intelligent log analysis and automated event correlation to speed up troubleshooting and root cause identification.
Develop and maintain incident management processes incorporating automated decision support systems to improve response times and minimize service disruptions.
Conduct post-incident reviews, using automated pattern recognition and trend analysis to identify systemic issues and implement preventive measures.
Analyze performance metrics and logs, supported by advanced observability tools, to detect bottlenecks and inefficiencies.
Collaborate with development teams to implement automated profiling and optimization recommendations for code and infrastructure improvements.
Perform capacity planning using machine learning forecasting models to ensure systems can handle current and future loads.
Develop and implement automation solutions, including intelligent runbook automation, self-healing systems, and automated incident triage.
Identify and drive process improvements by applying machine learning to operational data for continuous optimization.
Maintain documentation that includes automation and machine learning guidelines for monitoring, incident management, and SRE best practices.
Work closely with engineering, operations, and product teams to align reliability and monitoring goals, including automation adoption strategies.
Communicate effectively with stakeholders, providing regular updates on system health, incidents, performance improvements, and data-driven insights.
Foster a culture of collaboration, knowledge sharing, and automation best practices within the team and across the organization.