JOBSEARCHER

Quality Assurance Engineer

ComriseFoster City, CAApril 22nd, 2026
THIS IS A W2-Contract OPPORTUNITY. We are helping an on-demand, autonomous ride-hailing company hire a QA Engineer to ensure the reliability, performance, and scalability of backend systems supporting autonomous fleet operations.In this role, you’ll play a key part in maintaining high-quality system performance, directly impacting rider experience and the efficiency of fleet management operations.The ideal candidate is detail-oriented, technically strong, and experienced in backend testing and automation within complex systems. As a QA Engineer, you'll:Design and implement test plans and procedures for backend services supporting ride-hailing, charging, cleaning, fleet monitoring, and coordination systems.Validate APIs, services, and data models used by mobile apps, vehicles, and fleet management tools, and support their integration.Test vehicle agent components that bridge communication between onboard systems and backend services to ensure reliability and performance.Develop and execute automated test scripts to simulate multi-agent coordination, resource allocation, planning, and optimization workflows.Collaborate with engineering teams to ensure backend systems are scalable, observable, and fault-tolerant.Lead testing efforts such as ZPT triage, root cause analysis, release validation, and process improvements.Qualifications:Bachelor's degree in an engineering, math, or related field 3+ years of experience in quality assurance Experience with Python Experience writing scripts that exercise workflows Experience with APIs Understanding API documentation and specifications Experience analyzing backend logs for triaging issues and inclusion in bug reports Able to lead independent activities such as root cause analysis, process improvement, etc.Bonus Qualifications: Familiarity with Kubernetes, Docker, Java, Kotlin Masters degree in computer science or related degree Experience with customer-facing application experience Experience handling large data sets