About the role
As a Lead Performance Test Engineer, you will make an impact by leading and executing performance engineering initiatives for complex enterprise and cloud-native applications. This is a hands-on technical role requiring deep expertise in performance testing, automation, cloud platforms, observability, and application resiliency.
You will collaborate with development, architecture, platform engineering, DevOps, and Site Reliability Engineering teams to establish performance standards, implement automated quality gates, identify system bottlenecks, and improve application scalability and operational readiness.
In this role, you will:
Design and execute performance, load, stress, endurance, scalability, and capacity-testing strategies for enterprise applications, APIs, and cloud-based services.
Build and maintain automated performance-testing frameworks using NeoLoad and custom performance engineering solutions.
Integrate performance testing into CI/CD pipelines using GitLab CI/CD or comparable automation platforms, including performance thresholds and quality gates.
Analyze applications, database, infrastructure, network, and cloud performance to identify bottlenecks and provide actionable optimization recommendations.
Use AWS services and observability platforms such as CloudWatch, Dynatrace, Splunk, Grafana, and Prometheus to troubleshoot complex performance issues.
Plan and execute Chaos Engineering and resiliency-testing exercises to evaluate fault tolerance, recovery capabilities, and operational readiness.
Develop automation utilities using Python, Java, SQL, APIs, and scripting languages to improve testing efficiency and reduce manual effort.
Partner with technical and business stakeholders to define performance KPIs, engineering standards, capacity requirements, and performance-improvement plans.
Work model
We strive to provide flexibility wherever possible. Based on this role's business requirements, this is a Remote position open to qualified applicants in the United States for the duration of the assignment. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you are engaged in, as well as business and client requirements. Rest assured, we will always be clear about role expectations.
What you need to have to be considered
At least 10 years of hands-on experience in performance testing, performance engineering, or non-functional testing for enterprise applications.
Hands-on expertise with NeoLoad or a comparable enterprise performance testing tool, including test design, workload modeling, execution, analysis, and reporting.
Experience integrating automated performance tests into CI/CD pipelines using GitLab CI/CD or similar automation platforms.
Hands-on experience with AWS cloud services and cloud-native architectures, including services such as EC2, ECS, EKS, Lambda, RDS, S3, and CloudWatch.
Programming and scripting experience using Python, Java, SQL, and shell scripting, including experience testing REST APIs, microservices, and distributed systems.
Experience diagnosing performance issues across application, database, infrastructure, network, and cloud layers using observability tools such as Dynatrace, AppDynamics, Splunk, Grafana, Prometheus, or Elastic Stack.
Experience working with containerized environments and orchestration platforms such as Kubernetes, Docker, OpenShift, ECS, or EKS.
Strong communication, collaboration, and stakeholder-management skills, with the flexibility to support planned production testing during off-hours or weekends when required.
These will help you stand out
Experience designing and implementing Chaos Engineering, resiliency-testing, or disaster-recovery validation programs.
Knowledge of Site Reliability Engineering principles, operational excellence practices, service-level objectives, and performance-based quality gates.
Experience with capacity planning, scalability analysis, production-readiness assessments, and cloud-cost optimization.
Experience developing reusable performance engineering frameworks, accelerators, or custom automation utilities.
Exposure to AI-driven performance analysis, anomaly detection, root-cause analysis, predictive capacity planning, or intelligent test automation.
We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.
Salary and Other Compensation
The annual salary for this position is between $83,250 to $132,000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits
• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan
Cognizant will only consider applicants for this position who are legally authorized to work in the United States without company sponsorship.
*Please note, this role is not able to offer visa transfer or sponsorship now or in the future*
