Senior Quality Assurance Engineer

About Us At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges. From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future. Job Summary: As a Senior Quality Assurance Engineer at Hayden AI, you will drive quality through well-defined testing processes and disciplined release management for embedded software deployed in real-world transportation environments. You will be responsible for establishing and executing manual and automated test strategies, defining quality gates, managing regression cycles, and ensuring release readiness across embedded software versions. You will own the end-to-end quality process for embedded software releases, including test planning, risk assessment, defect triage, release sign-off, and post-release validation. Working closely with Software Engineers, Product Managers, and Operations teams, you will embed quality into the development lifecycle, improve testing workflows, and support reliable field deployments through structured validation and continuous process improvement. Responsibilities: Take ownership of end-to-end quality for vital embedded software, overseeing the planning, execution, and final approval of releases through a mix of rigorous manual testing and automation-first methodologies Orchestrate the embedded software release lifecycle, including defining test strategies, ensuring schedule alignment, assessing risks, and leading go/no-go evaluations in partnership with engineering and product teams Establish, execute, and iterate on comprehensive validation strategies for embedded systems, edge hardware, and complex system integrations Architect and maintain robust Python-based automation frameworks to streamline regression, smoke testing, and release validation efforts Direct release test cycles by managing regression execution, facilitating defect triage, and providing detailed reports on release readiness Implement automated and manual suites within CI/CD pipelines to maintain stringent quality gates across all embedded software versions Validate intricate system behaviors involving embedded devices, hardware interfaces, sensor data, and event-driven logic Investigate complex defects through root cause analysis, championing preventative measures and driving sustainable quality enhancements Collaborate with Embedded Software Engineers during the design phase to advocate for testability, reliability, and expanded automation coverage Develop and monitor quality metrics and dashboards to provide stakeholders with transparency regarding release health and long-term trends Ensure successful field deployments by validating device stability, environmental performance, and reliability throughout the release cycle Guide junior engineers and offer strategic leadership to scale quality workflows, documentation standards, and technical best practices across the engineering org Required Qualifications: Experience: Minimum of 7 years in Quality Assurance, Test Engineering, or SDET roles, with a focus on structured testing and software validation Core Skills: Experience testing devices, embedded systems, or IoT platforms Strong proficiency in Python for building and maintaining automated test frameworks Experience with system-level, integration, and end-to-end automation Solid understanding of SDLC, CI/CD pipelines, and automation-first QA methodologies Familiarity with video pipelines, streaming systems, or sensor-driven workflows Experience with test management, defect tracking, and release processes Strong communication and cross-functional collaboration skills Personal Attributes: [Communication, collaboration, adaptability, problem-solving attributes] Education: Bachelor’s degree in Computer Science, Engineering, or equivalent experience Preferred Qualifications: Experience testing AI/ML-driven systems, including model validation, data quality checks, and performance monitoring in production environments Familiarity with backend services and distributed systems to support system-level and integration testing Hands-on experience with observability and reporting tools such as Grafana, Datadog, or similar platforms for quality metrics, monitoring, and release health reporting