Quality Engineering Lead

NYU Langone Health•New York, NY

1d•$121,792 - $158,998

About The Position

We have an exciting opportunity to join our team as a Quality Engineering Lead. We are looking for a Quality Engineering Lead who will serve as a strong hands-on technical resource across enterprise projects. This role is focused on technical testing, automation, framework evaluation, AI in Quality, technical innovation, and stakeholder engagement. The role is intended for someone who can quickly understand the existing QA landscape, identify technical gaps and opportunities, and help the QA organization adopt better tools, frameworks, and engineering practices.

Requirements

5 years experience in Software Quality Assurance
Qualified candidates must be able to effectively communicate with all levels of the organization.

Responsibilities

Own QA delivery, quality outcomes, timelines, and release readiness for assigned enterprise projects.
Define the technical testing strategy, approach, scope, priorities, and execution plan.
Manage, guide, and oversee offshore QA resources throughout project delivery.
Provide technical direction to offshore resources and ensure execution aligns with defined testing standards, automation strategy, quality expectations, and project objectives.
Monitor offshore execution, identify risks and blockers, and drive issues to resolution.
Remain technically hands-on and provide expertise in technical testing, automation, API, integration, backend, database, and end-to-end testing.
Assess existing automation frameworks, architecture, tools, and technical challenges; identify opportunities to enhance or introduce new solutions, conduct POCs to validate technical approaches, and provide recommendations that improve the overall QA capability.
Provide hands-on technical expertise to design, develop, enhance, and implement automation solutions and frameworks across UI, API, integration, regression, and end-to-end testing, including complex enterprise applications, integrations, backend systems, databases, and distributed architectures.
Support and drive QA delivery across enterprise-level technology transformation programs, modernization initiatives, and other complex enterprise programs.
Define, build, and continuously evolve the organizations AI QA capabilities and AI Quality Engineering framework, establishing the strategy, technical architecture, standards, governance, use cases, and implementation approach for applying AI across the testing lifecycle.
Provide hands-on technical expertise to develop, validate, and implement AI-enabled QA capabilities, including AI-assisted test design, test generation, automation, test data, defect analysis, regression optimization, quality insights, and other emerging AI testing applications.
Identify and recommend opportunities to improve QA efficiency, automation, coverage, quality, and engineering practices.
Work directly with business, technology, architecture, product, and program stakeholders.
Strong performance testing / performance engineering expertise, including workload modeling, scripting, execution, monitoring, bottleneck analysis, and performance reporting.
Communicate technical risks, findings, recommendations, and opportunities clearly to technical and non-technical stakeholders.
Provide technical guidance, thought leadership, and recommendations to the broader QA team.
Stay current with modern automation, testing, AI, and quality engineering practices.