Performance Quality Engineer

8am is a professional business platform that empowers client-focused professionals with innovative technology. They are seeking a Performance Quality Engineer to drive performance observability, define metrics, and collaborate with engineering teams to mitigate performance risks before they affect customers.

Responsibilities:

• Design and create performance test suites for multiple product teams against a microservices-based SaaS platform running on AWS
• Operate and help maintain production-like environments for performance analysis, diagnosis, and regression testing
• Analyze application and infrastructure logs to identify, isolate, and help root-cause performance degradations
• Define, track, and report on performance KPIs (response times, throughput, error rates, resource utilization) and deliver trend analysis and projections to engineering leadership and product stakeholders
• Use usage and trend data to identify capacity risks and provide recommendations before they impact customers
• Collaborate with Platform Engineering, DevX, SDET, and Product teams to prioritize and validate performance improvements
• Partner with Security QE on the overlap between performance and security risk. Load and stress tests reveal how systems degrade under pressure, which is exactly what attackers exploit via DoS and resource-exhaustion vectors. This role will collaborate with Security QE to integrate security-informed scenarios (authentication storms, TLS renegotiation abuse, API rate-limit validation) into performance test plans, and surface high-resource-cost endpoints to security for assessment
• Identify and define nonfunctional performance tests for CI/CD pipeline gates (Integration, Regression, Post-Deployment). Work with DevX and Platform Engineering to establish pass/fail thresholds that catch regressions before production
• Contribute to performance engineering standards, runbooks, and best practices within the QE organization

Requirements:

• 3+ years of hands-on performance testing and analysis on microservices-based, cloud-hosted (AWS) SaaS platforms
• Strong analytical skills with a demonstrated ability to move from symptoms to root cause
• Background in statistical analysis: trend modeling, interpolation, extrapolation, and capacity forecasting
• Working knowledge of AWS (EC2, RDS, S3, ECS/EKS), Docker, and Kubernetes
• Experience with performance testing tools (k6, Gatling, Locust, JMeter, or equivalent)
• Experience with observability platforms (Prometheus, Grafana, Datadog) and log aggregation (ELK Stack, CloudWatch)
• Scripting proficiency in Python or comparable language for test scenarios, data analysis, and light tooling
• Comfortable working asynchronously across multiple time zones in a remote-first team
• Demonstrated experience leveraging AI tools and technologies to improve workflows, enhance decision-making, or drive innovation