Quality Assurance Engineer

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