Quick overview
SeniorityMid Senior
Work modeHybrid
LocationNew York, NY, United States
BashDatadogGoogle CloudGrafanaPrometheusPythonTerraformKubernetesCI/CDLinux
Job description
Infrastructure Engineer — Performance & Load Testing
NYC, NY
Job Summary
We are seeking an Infrastructure Engineer specializing in Performance and Load Testing to design, provision, and maintain scalable test environments used to evaluate the performance, reliability, and scalability of distributed applications. This role will focus on Google Cloud Platform and Kubernetes infrastructure, test-environment configuration, data seeding, automated test execution, workload orchestration, and observability.
The ideal candidate has strong cloud and Kubernetes expertise, understands performance-testing workflows, and can build reliable infrastructure that enables engineering teams to execute realistic, repeatable, and production-like load tests.
NYC, NY
Job Summary
We are seeking an Infrastructure Engineer specializing in Performance and Load Testing to design, provision, and maintain scalable test environments used to evaluate the performance, reliability, and scalability of distributed applications. This role will focus on Google Cloud Platform and Kubernetes infrastructure, test-environment configuration, data seeding, automated test execution, workload orchestration, and observability.
The ideal candidate has strong cloud and Kubernetes expertise, understands performance-testing workflows, and can build reliable infrastructure that enables engineering teams to execute realistic, repeatable, and production-like load tests.
Key Responsibilities
• Design, provision, configure, and maintain Google Cloud Platform-based performance and load-testing environments.
• Deploy and manage Kubernetes clusters, namespaces, workloads, services, networking, and supporting infrastructure.
• Build repeatable infrastructure configurations using Infrastructure as Code (IaC) tools such as Terraform.
• Configure test environments to closely replicate relevant production architectures, dependencies, and workloads.
• Develop automated processes for test-environment setup, configuration, teardown, and reset.
• Prepare and seed test databases and application environments with realistic datasets required for performance testing.
• Automate data generation, loading, cleanup, and refresh processes between test runs.
• Configure and trigger load and performance tests across distributed environments.
• Integrate performance testing into CI/CD pipelines and automated engineering workflows.
• Develop mechanisms to schedule, trigger, monitor, and terminate performance-test workloads.
• Configure Kubernetes resources to support high-concurrency and high-throughput testing scenarios.
• Monitor infrastructure and application behavior during load tests using Grafana, Prometheus, Datadog, and related observability platforms.
• Develop dashboards and alerts for key infrastructure and application metrics.
• Analyze CPU, memory, network, storage, pod, node, database, and service-level metrics to identify infrastructure bottlenecks.
• Support correlation of infrastructure metrics with performance indicators such as latency, throughput, concurrency, and error rates.
• Troubleshoot infrastructure-related performance issues and work with Software Engineers, QA Engineers, SRE, and DevOps teams on remediation.
• Maintain documentation for test-environment architecture, deployment procedures, test execution workflows, and observability configurations.
• Ensure performance-testing infrastructure is reliable, scalable, reproducible, and cost-conscious.
• Design, provision, configure, and maintain Google Cloud Platform-based performance and load-testing environments.
• Deploy and manage Kubernetes clusters, namespaces, workloads, services, networking, and supporting infrastructure.
• Build repeatable infrastructure configurations using Infrastructure as Code (IaC) tools such as Terraform.
• Configure test environments to closely replicate relevant production architectures, dependencies, and workloads.
• Develop automated processes for test-environment setup, configuration, teardown, and reset.
• Prepare and seed test databases and application environments with realistic datasets required for performance testing.
• Automate data generation, loading, cleanup, and refresh processes between test runs.
• Configure and trigger load and performance tests across distributed environments.
• Integrate performance testing into CI/CD pipelines and automated engineering workflows.
• Develop mechanisms to schedule, trigger, monitor, and terminate performance-test workloads.
• Configure Kubernetes resources to support high-concurrency and high-throughput testing scenarios.
• Monitor infrastructure and application behavior during load tests using Grafana, Prometheus, Datadog, and related observability platforms.
• Develop dashboards and alerts for key infrastructure and application metrics.
• Analyze CPU, memory, network, storage, pod, node, database, and service-level metrics to identify infrastructure bottlenecks.
• Support correlation of infrastructure metrics with performance indicators such as latency, throughput, concurrency, and error rates.
• Troubleshoot infrastructure-related performance issues and work with Software Engineers, QA Engineers, SRE, and DevOps teams on remediation.
• Maintain documentation for test-environment architecture, deployment procedures, test execution workflows, and observability configurations.
• Ensure performance-testing infrastructure is reliable, scalable, reproducible, and cost-conscious.
Required Qualifications
• Bachelor's degree in computer science, Information Technology, Engineering, or a related technical field.
• 6+ years of experience in Infrastructure Engineering, DevOps, SRE, Cloud Engineering, or a related role.
• Strong hands-on experience with Google Cloud Platform (Google Cloud Platform).
• Strong experience with Kubernetes and containerized applications.
• Experience deploying and troubleshooting distributed applications in cloud environments.
• Experience with Infrastructure as Code, particularly Terraform or equivalent technologies.
• Strong Linux and networking fundamentals.
• Experience automating infrastructure and operational workflows using Python, Bash, Go, or similar languages.
• Experience configuring and managing monitoring and observability systems.
• Understanding of performance-testing concepts including load, stress, endurance, scalability, concurrency, throughput, and latency.
• Strong troubleshooting and root-cause-analysis skills.
• Bachelor's degree in computer science, Information Technology, Engineering, or a related technical field.
• 6+ years of experience in Infrastructure Engineering, DevOps, SRE, Cloud Engineering, or a related role.
• Strong hands-on experience with Google Cloud Platform (Google Cloud Platform).
• Strong experience with Kubernetes and containerized applications.
• Experience deploying and troubleshooting distributed applications in cloud environments.
• Experience with Infrastructure as Code, particularly Terraform or equivalent technologies.
• Strong Linux and networking fundamentals.
• Experience automating infrastructure and operational workflows using Python, Bash, Go, or similar languages.
• Experience configuring and managing monitoring and observability systems.
• Understanding of performance-testing concepts including load, stress, endurance, scalability, concurrency, throughput, and latency.
• Strong troubleshooting and root-cause-analysis skills.
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