Software Engineer - Performance and Tools

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineer - Performance and Tools based in the United States. This role is ideal for a software engineer who enjoys solving complex performance challenges and building tools that improve enterprise application reliability. You will work across software development, performance engineering, test automation, observability, databases, and cloud-native systems. The position combines hands-on engineering with investigation of application, infrastructure, and database bottlenecks. You will help develop synthetic test data solutions, create sophisticated performance test frameworks, and validate system scalability under demanding conditions. Working closely with Development, QA, DevOps, and SRE teams, you’ll turn performance insights into practical engineering improvements. The role also offers opportunities to apply AI/ML techniques and modern observability practices to performance testing and analysis. As part of a collaborative remote engineering environment, you’ll contribute directly to the reliability and scalability of technology supporting the healthcare industry. Performance engineering: Design, develop, and execute performance testing scenarios covering load, stress, spike, endurance/soak, volume, and scalability testing. Performance troubleshooting: Investigate application performance issues by analyzing application, infrastructure, and database bottlenecks and identifying root causes. Test data engineering: Support development and quality teams with test data requirements, maintain internal synthetic data generation tools, and enhance their capabilities. Test automation: Develop, maintain, and optimize performance scripts, test frameworks, and supporting automation. CI/CD integration: Integrate performance testing into continuous integration and deployment pipelines to make performance validation part of the software delivery lifecycle. Observability: Incorporate monitoring and observability tools into performance analysis, using logs, metrics, traces, dashboards, and alerts to diagnose issues. AI-enabled engineering: Develop solutions using an AI-centric approach and explore AI/ML techniques that can improve performance testing, analysis, and engineering workflows. Cross-functional collaboration: Partner with Development, QA, DevOps, and SRE teams to identify, communicate, and resolve performance and scalability issues. Performance reporting: Build performance reports and reporting frameworks and provide actionable recommendations for application optimization. Application scalability: Validate and improve the scalability, reliability, and performance of enterprise applications and cloud-native systems. Continuous improvement: Identify opportunities to improve performance engineering practices, tooling, automation, and overall testing efficiency. Requirements: Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field. Professional experience: 3–8 years of experience spanning software development and performance testing or performance engineering. Python: Professional experience using Python for backend application development. JavaScript: Basic experience with JavaScript for frontend web development. SQL and databases: Experience with SQL, database design principles, query development and optimization, and database performance analysis. AI development tools: Experience using AI-assisted development tools such as Claude or GitHub Copilot to produce high-quality engineering solutions. Performance testing: Practical understanding of performance engineering concepts and hands-on experience with one or more tools such as JMeter, LoadRunner, Gatling, k6, Locust, NeoLoad, or BlazeMeter. Observability and monitoring: Experience with platforms such as Datadog, AppDynamics, Dynatrace, New Relic, Grafana, OpenTelemetry, AWS CloudWatch, or Google Cloud Monitoring.