Java SRE Engineer: AI-Enhanced Reliability & Observability

Ampstek; Phoenix (AZ); On-site; USD 90,000 - 130,000; Full time

Job summary

Ampstek is seeking a hands-on Java and SRE Engineer to strengthen our application development, production support, and observability capabilities. You will work on Java/Spring Boot applications, implement robust monitoring, and troubleshoot across the stack using modern AI-assisted tooling.

The role emphasizes improving reliability, incident response, and automation within Kubernetes/OpenShift environments and enterprise Linux systems.

Qualifications

• Proficient in Java and Spring Boot with solid fundamentals.
• Experience building and supporting enterprise applications.
• Strong background in production support, observability, and troubleshooting.

Responsibilities

• Develop, troubleshoot, and support enterprise Java applications (Java/J2EE, Spring Boot, REST APIs, microservices).
• Provide SRE and production engineering support for critical services.
• Troubleshoot complex production issues across app, API, infra, database, and network layers.
• Perform RCA and drive corrective actions for recurring incidents.
• Support incident, problem, and change management and meet SLA/SLOs.
• Monitor health using Splunk/Elasticsearch/Kibana; create dashboards and alerts.
• Manage apps running on Kubernetes/OpenShift and enterprise Linux.
• Work with CI/CD pipelines, release processes, and production validation.
• Identify opportunities to automate repetitive operational activities.
• Use AI-assisted tools for debugging, log analysis, and automation.
• Ramp up quickly on new apps, technologies, and support processes.

Skills

Java

Spring Boot

REST APIs

Microservices

SRE

Observability

Kubernetes/OpenShift

Linux

CI/CD

AI-assisted engineering tools

Tools

Splunk

Elasticsearch

Kibana

Job description

Ampstek is seeking a hands-on Java and SRE Engineer to strengthen our application development, production support, and observability capabilities. You will work on Java/Spring Boot applications, implement robust monitoring, and troubleshoot across the stack using modern AI-assisted tooling.

The role emphasizes improving reliability, incident response, and automation within Kubernetes/OpenShift environments and enterprise Linux systems.