[Hiring] QA Automation Lead (Performance Testing) @Juniper Square

Role Description

As a QA Automation Lead for Performance testing at Juniper Square, you will define the performance engineering strategy for the organization. You will ensure our systems can handle hyper-growth and peak traffic events through proactive modeling, automated gating, and deep architectural analysis.

• Review functional and non-functional requirements, technical design documents, and provide meaningful feedback to identify performance risks early.
• Design, develop, and execute performance, load, and stress tests for web and backend systems.
• Use AI to analyze production traffic patterns and automatically generate representative performance scripts in Locust or JMeter that mirror real-world user behavior.
• Build and maintain performance test scripts using Python, primarily leveraging Locust (tool-agnostic mindset, but Locust experience is a strong plus).
• Collaborate closely with development, QA, DevOps, and SRE teams to define performance benchmarks, SLAs, and acceptance criteria.
• Analyze test results to identify bottlenecks related to application code, APIs, databases, infrastructure, or third-party dependencies.
• Produce clear and actionable performance test reports, highlighting trends, risks, and recommendations for optimization.
• Integrate performance tests into CI/CD pipelines and support continuous performance testing practices.
• Monitor application performance during releases and contribute to capacity planning and scalability discussions.
• Lead performance engineering best practices and help shift performance testing left in the SDLC.

Qualifications

• Bachelor's degree in Computer Science, or equivalent professional experience.
• 7-10 years in Software Quality Assurance, with at least 5 years focused on performance, load, stress, and endurance testing.
• Strong hands-on experience designing and executing performance test strategies for web applications and APIs with an ability to read architectural diagrams and identify potential single points of failure.
• Strong proficiency in Python, with the ability to write clean, maintainable, and scalable test code.
• Experience with performance testing tools such as Locust (preferred), JMeter, Gatling, or similar.
• Solid understanding of performance metrics (response time, throughput, latency, error rates, resource utilization) and profiling techniques.
• Hands-on experience testing REST APIs and backend services under load.
• Experience designing and owning the Performance Gate in the CI/CD pipeline, ensuring automated performance regressions are caught before reaching production.
• Advanced skills in using APM tools (e.g., Datadog, New Relic, or Dynatrace) and profiling tools to pinpoint code-level bottlenecks, memory leaks, and thread contention.
• Experience managing large-scale, sanitized test data sets required for high-volume performance execution without skewing cache results.
• Deep experience with AWS infrastructure (EC2, Lambda, RDS, ELB), and containerization (Docker, Kubernetes).
• Experience in performance test plans, scenarios, workload models, and test data strategies.
• Excellent analytical and problem-solving abilities, attention to detail, and the ability to work independently within Agile development teams.
• Clear written and verbal communication skills, with the ability to explain performance findings to both technical and non-technical stakeholders.

AI Qualifications

• Experience designing evaluation frameworks for LLM-powered features, including prompt regression testing and behavioral drift detection.
• Proactively leverage AI tools (e.g., Cursor, Gemini) to accelerate test authoring, debugging, and maintenance of automation frameworks.
• Use AI to diagnose failures, generate test scenarios, and improve coverage and efficiency.
• Contribute to testing strategies for AI-powered features, including validation of LLM outputs, edge cases, and reliability.
• Drive best practices for the ethical and effective use of AI tools within QA workflows and across the broader engineering team.