Site Reliability Engineer (SRE)

ATLANTICUS•Atlanta, GA

5d•$100,000 - $115,000•Onsite

About The Position

When you join Atlanticus, you become a member of a fast-growing, mission-focused company that is committed to aid in meeting the financial needs of middle-class Americans. With a culture of collaboration and a one-team mindset, we encourage entrepreneurial thinking to empower our customers toward financial well-being. Atlanticus™ technology enables bank, retail, and healthcare partners to offer more inclusive financial services to everyday Americans through the use of proprietary analytics. We apply the experience gained and infrastructure built from servicing over 20 million customers and over $40 billion in consumer loans over more than 25 years of operating history to support lenders that originate a range of consumer loan products. These products include retail and healthcare, private label credit and general-purpose credit cards marketed through our omnichannel platform, including retail point-of-sale, healthcare point-of-care, direct mail solicitation, digital marketing, and partnerships with third parties. Additionally, through our Auto Finance subsidiary, Atlanticus serves the individual needs of automotive dealers and automotive non-prime financial organizations with multiple financing and service programs. We foster a collaborative, innovative environment where everyone contributes to building something meaningful. You’ll be empowered to lead, grow, and make an impact. The Role We are seeking a Site Reliability Engineer (SRE) to ensure the reliability, availability, performance, and operational excellence of our cloud-native applications running on AWS. This is a hands-on role responsible for monitoring and supporting production systems, automating operational tasks, managing deployments, and driving continuous improvements in system stability. The ideal candidate has strong experience supporting Java-based applications running on Amazon EKS, a solid understanding of AWS infrastructure, and expertise with observability platforms such as Datadog and Splunk. This role requires participation in a 24x7 production support and on-call rotation, working closely with Development, DevOps, IT Ops, Database, Network, and Security teams to maintain highly available production services. The successful candidate should be passionate about automation, troubleshooting complex production issues, improving application reliability, and leveraging AI-powered tools to enhance operational efficiency.

Requirements

5+ years of experience supporting production applications in an SRE, DevOps, Production Support, or Site Reliability Engineering role.
Strong experience supporting Java-based applications in production environments.
Hands-on experience with AWS services including EKS, EC2, ALB/NLB, RDS, IAM, Route 53, CloudWatch, S3, and VPC.
Experience with Kubernetes (Amazon EKS), Docker, and containerized application deployments.
Strong experience using Datadog / Splunk for infrastructure monitoring, APM, troubleshooting, dashboards, alerting, and log analysis.
Experience performing production deployments through CI/CD pipelines (Jenkins, GitHub Actions, Argo CD, or similar).
Experience supporting MySQL and Oracle databases from an application support perspective.
Proficiency in Python, Bash, or other scripting languages for automation.
Strong Linux system administration and troubleshooting skills.
Excellent troubleshooting skills across distributed applications, networking, and cloud infrastructure.
Knowledge of networking fundamentals including DNS, TCP/IP, HTTP/HTTPS, TLS, load balancing, and firewalls.
Experience with incident management, problem management, and change management processes.
Experience using AI-assisted development tools or agentic AI systems to improve operational efficiency.

Nice To Haves

Experience with Helm and GitOps deployment models.
Experience with Terraform or Infrastructure as Code.
Familiarity with Prometheus, Grafana, or OpenTelemetry.
Experience supporting microservices architectures.
Knowledge of JVM tuning and Java performance optimization.
Experience with AWS Auto Scaling, Karpenter, or Cluster Autoscaler.

Responsibilities

Provide 24x7 production support through an on-call rotation to ensure application availability and rapid incident response.
Continuously monitor production applications, infrastructure, and platform health using Datadog, Splunk, CloudWatch, and other monitoring tools.
Respond to production incidents, troubleshoot issues, and restore services while minimizing customer impact.
Perform root cause analysis (RCA) and implement corrective actions to prevent recurring incidents.
Deploy and support Java-based applications running on Docker and Amazon EKS using CI/CD pipelines.
Execute production deployments, application releases, hotfixes, and rollbacks following change management processes.
Monitor and manage scheduled application jobs, batch processes, and integrations to ensure successful execution.
Troubleshoot Java application issues using logs, JVM metrics, thread dumps, heap dumps, and application performance metrics.
Analyze application, infrastructure, and Kubernetes logs using Splunk and Datadog to identify performance bottlenecks and operational issues.
Develop automation scripts using Python, Bash, or similar scripting languages to eliminate repetitive operational tasks.
Build self-healing and automated operational processes to improve system reliability and reduce manual intervention.
Support Kubernetes (Amazon EKS) environments, including troubleshooting pods, deployments, networking, ingress, and scaling issues.
Maintain and improve dashboards, alerts, Service Level Indicators (SLIs), Service Level Objectives (SLOs), and operational runbooks.
Partner with Development teams to improve application reliability, resiliency, scalability, and performance.
Continuously improve operational processes, monitoring coverage, automation, and deployment practices.
Leverage AI-powered engineering tools and agentic AI capabilities to improve monitoring, incident response, automation, and operational efficiency.