Sr SDET - Performance Testing

About the Role:
HighLevel is looking for a Sr. SDET with 5+ years of experience to play a crucial role in ensuring the quality, performance, and scalability of our products. We are seeking engineers who thrive in a fast-paced startup environment, enjoy problem-solving, and stay updated with the latest models and solutions. This is a great opportunity to work on cutting-edge performance testing strategies and contribute to the success of our products.

Responsibilities:
Performance baselines for critical services: SLIs, SLOs, and latency, throughput, and error-rate targets, plus workload models built from production traffic and real customer behaviour A shared performance testing framework and production-like environments (Kubernetes and cloud, test data included) that product-team SDETs can use without starting from scratch, and the evaluation of new tools through PoCs Automated performance regression checks in CI/CD, with trend reports that catch regressions before release Load, stress, soak, and spike testing, and capacity planning ahead of peak events Root cause analysis of bottlenecks across API, database, queue, and frontend layers, using traces, metrics, logs, and profiling, in partnership with development, DevOps, and infrastructure teams Strong understanding of distributed systems, microservices architecture, concurrency, rate limiting and common performance bottlenecks Ability to interpret performance metrics, translate findings into actionable engineering recommendations, and influence technical decisions across engineering teams Supervise and mentor junior team members and contribute to capability building initiatives to raise the performance bar across the team

Requirements:
5+ years in performance, scalability, or reliability engineering or testing, with examples of finding and fixing bottlenecks in production-scale systems Hands-on experience with at least one modern load-testing tool (k6, Gatling, or Locust), including realistic workload modeling and distributed load generation, and strong programming skills in Python, JavaScript/TypeScript, or Java Experience using observability tooling (for example New Relic, Prometheus/Grafana, OpenTelemetry) to isolate root cause across API, database, and queue layers, with a solid grasp of REST service performance, concurrency, and caching Experience integrating performance tests into CI/CD pipelines with pass/fail thresholds Working knowledge of Kubernetes and at least one major cloud (GCP, AWS, or Azure) to deploy and debug test environments

Nice to Have:
Runtime profiling and thread or heap analysis on the JVM or Node.js (GC behavior, event-loop lag) Frontend performance experience: Core Web Vitals, Lighthouse, real user monitoring Experience applying AI-assisted tooling to test design or result analysis Experience with NoSQL or search datastores and message brokers at scale Chaos or resilience testing, and safe testing in production (canaries, shadow traffic)

EEO Statement:
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