Software Engineer II (IN) Senior (Automation Testing with Gen AI)

Role Overview

Leadership and Test Strategy

• Define, own, and execute the comprehensive test strategy for the Edge AI and mobile ecosystem.
• Lead, mentor, and task-manage QA automation engineers.
• Collaborate with product managers, ML researchers, and hardware engineers on quality gates and acceptance criteria.
• Report quality metrics, test coverage, and release readiness to senior management and stakeholders.

Edge Device Validation

• Validate deployment, stability, and inference accuracy of AI models running on NVIDIA Jetson edge devices.
• Benchmark model performance, system impact, thermal behavior, inference latency, and concurrent-user performance.

Computer Vision Testing

• Use OpenCV to augment video test data with synthetic conditions and edge cases.
• Use automated video annotation tools such as CVAT to build, manage, and refine ground-truth datasets.

Mobile and Automation Testing

• Architect manual and automated testing for Android applications, including UI/UX, BLE/Wi-Fi connectivity, and real-time data streaming.
• Design scalable test frameworks for mobile and embedded Linux or edge platforms using Appium, Espresso, Python, and Pytest.
• Integrate automated tests into CI/CD pipelines such as Jenkins and GitLab CI.

Performance and AI-Driven Testing

• Architect load, stress, and endurance tests for high-throughput environments and concurrent edge-to-cloud connections.
• Identify architectural bottlenecks and measure system latency using tools such as JMeter.
• Drive adoption of AI testing tools and use Weights & Biases to track model evaluation metrics across builds.

Required Qualifications

• 7+ years of experience in software quality assurance, systems or solutions testing, or SDET roles.
• At least 2+ years in a lead, principal, or QA management position.
• Expert-level Linux knowledge for embedded systems, edge deployments, and hardware-software integration.
• Extensive embedded Linux, IoT, or edge hardware testing experience, including direct NVIDIA Jetson experience.
• Advanced performance testing knowledge and hands-on JMeter experience.
• Strong mobile automation architecture knowledge for Android and iOS.
• Advanced Python skills and familiarity with Java or Kotlin.
• Solid knowledge of TCP/IP, MQTT, REST, WebRTC, and RTSP.

Preferred Qualifications

• Experience with NVIDIA SDKs such as TensorRT, DeepStream, or CUDA.
• Advanced experience testing high-throughput video streaming applications.
• Familiarity with Docker and Kubernetes on edge devices.

Workplace and Flexibility

• The employer describes hybrid work and adaptable hours as part of its team flexibility offerings.