Onsite Performance Engineer - Load & Scalability

Tech Mirrors; San Antonio (TX); On-site; USD 62,000 - 66,000; Full time

Job summary

Tech Mirrors in San Antonio, TX is hiring a Performance Tester for a long-term onsite contract. You will design and execute load, stress, endurance, and benchmark tests for distributed applications, driving performance improvements across the stack.

You will work with Java-based services, APIs, and message queues, integrate testing into CI/CD pipelines, and use OpenShift/Kubernetes and observability tools to identify bottlenecks and optimize performance.

Qualifications

• Experience designing and executing load, stress, endurance, and benchmark tests.
• Strong knowledge of Java, APIs, microservices, and messaging queues.
• Experience integrating performance testing into CI/CD pipelines and shift-left testing.
• Familiarity with OpenShift/Kubernetes or similar platforms and cloud environments.

Responsibilities

• Experience developing performance engineering standards, strategies, and best practices.
• Expertise designing and executing load, stress, endurance, scalability, and benchmark testing for distributed applications.
• Advanced root cause analysis using JVM analysis, thread dumps, heap dumps, DB diagnostics, and observability tools.
• Experience leading complex performance investigations and influencing architecture and infra decisions.
• Proven ability to lead performance testing efforts in CI/CD contexts.

Skills

Java

APIs

Microservices

CI/CD

Shift-left testing

Observability

Troubleshooting

Tools

StresStimulus

JMeter

Loadrunner

Gatling

k6

Splunk

OpenTelemetry

Dynatrace

OpenShift/Kubernetes

Microsoft Copilot

Job description

Tech Mirrors in San Antonio, TX is hiring a Performance Tester for a long-term onsite contract. You will design and execute load, stress, endurance, and benchmark tests for distributed applications, driving performance improvements across the stack.

You will work with Java-based services, APIs, and message queues, integrate testing into CI/CD pipelines, and use OpenShift/Kubernetes and observability tools to identify bottlenecks and optimize performance.