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Infrastructure Engineer Performance & Load Testing

Diverse LynxNew York, New York🇺🇸United States

Quick overview

Salary$110k - $120k/yr
SeniorityMid Senior
Employment typeFull Time
Work modeHybrid
LocationNew York, New York, United States
Stakeholder ManagementMicroservicesDatadogGatlingGoogle CloudGrafanaPrometheusTerraformk6KubernetesCI/CDLinux

Job description

Job Description Job Description Job Title:Infrastructure Engineer Performance & Load Testing
Location: New York, NY
Duration: Fulltime Job
Skills:Performance Testing
Salary: 110K-120K/Year
Required Skills & Qualifications:
Must Have Technical/Functional Skills
  • We are seeking a Senior Infrastructure Engineer to build and manage the infrastructure required for large-scale performance testing of a high-volume transactional platform. The ideal candidate will own test environment provisioning, distributed load generation infrastructure, observability, and test execution automation within cloud-native environments.
  • Hands-on performance and load testing experience is essential. We are seeking senior specialists, not generalist Infrastructure, DevOps, or Platform Engineers. Familiarity with tools such as k6 (preferred), Locust, Gatling, distributed load generation, and modern observability stacks is required.

Mandatory Expectations
  • Hands-on Performance & Load Testing experience is non-negotiable.
  • We are seeking top-tier senior specialists, not generalist engineers.
  • Deep expertise with k6 is preferred; experience with Locust, Gatling, or similar frameworks is required.
  • Experience performing large-scale distributed load generation.
  • Strong understanding of performance engineering principles including scalability, resiliency, throughput, latency analysis, and bottleneck identification.
  • Hands-on experience with modern observability tooling including Grafana, Prometheus, Datadog, OpenTelemetry, distributed tracing, and APM platforms.
  • Experience working with cloud-native, microservices-based, event-driven architectures.
  • Proven ability to identify, analyze, and remediate complex performance issues across application, messaging, database, and infrastructure layers.

Technical Skills
  • 7 years of Infrastructure, Platform Engineering, DevOps, or Site Reliability Engineering experience.
  • Strong hands-on experience supporting performance and load testing environments.
  • Deep expertise in Google Cloud Platform (Eligible to workP) and Kubernetes (GKE).
  • Experience building and managing distributed load testing infrastructure.
  • Hands-on knowledge of k6, Locust, Gatling, and distributed test execution platforms.
  • Strong understanding of cloud-native architectures, containerization, and microservices.
  • Expertise with Infrastructure as Code using Terraform or similar tools.
  • Experience provisioning and managing scalable test environments and automated data seeding solutions.
  • Advanced knowledge of observability platforms including Grafana, Prometheus, Datadog, OpenTelemetry, distributed tracing, and APM tools.
  • Strong Linux administration and infrastructure automation skills.
  • Experience with CI/CD pipelines and automated test orchestration.

Functional Skills
  • Infrastructure scalability and reliability planning.
  • Performance engineering support and Eligible to workimization.
  • Capacity planning and resource management.
  • Infrastructure troubleshooting and root cause analysis.
  • Automation-first mindset.
  • Cross-functional collaboration and technical leadership.
  • Strong communication and stakeholder management skills.

Roles & Responsibilities
  • Design, provision, and maintain production-like performance testing environments in Eligible to workP.
  • Build and manage Kubernetes-based infrastructure supporting large-scale distributed load testing.
  • Configure and Eligible to workimize distributed load generation frameworks and execution environments.
  • Automate environment provisioning, configuration, test execution, and teardown processes.
  • Develop and maintain test data generation and seeding strategies.
  • Implement and manage observability solutions to monitor platform behavior during performance tests.
  • Support performance test execution and troubleshooting across engineering teams.
  • Monitor system health, infrastructure utilization, and scalability metrics during testing activities.
  • Identify infrastructure bottlenecks and recommend remediation strategies.
  • Partner with QA and Software Engineering teams to ensure reliable and repeatable performance testing processes.
  • Continuously improve platform scalability, reliability, and performance testing capabilities.

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