Manager, Engineering Excellence & Quality Engineering

The Manager, Engineering Excellence & Quality Engineering is responsible for supporting and executing Fortrea's Engineering Excellence and Quality Engineering practices across the Global Digital Foundry organization. This leader drives engineering maturity by supporting standards, AI-enabled quality engineering practices, software craftsmanship, test automation, engineering governance, performance engineering, developer productivity, and continuous improvement initiatives that improve software quality, delivery effectiveness, and customer outcomes. Working closely with Product Engineering, Architecture, Platform Engineering, DevOps, Security, Data & AI, and Product Management, this role champions modern engineering practices that enable teams to build secure, scalable, reliable, and high-quality software. The role supports Engineering Excellence practices by helping drive standardization, automation, measurement, AI-assisted software engineering, and continuous improvement across the software development lifecycle. Summary of Responsibilities: Support and execute Fortrea's Engineering Excellence and Quality Engineering strategy, roadmap, standards, governance model, and operating framework. Build, lead, mentor, and develop high-performing Quality Engineering professionals while fostering technical growth, leadership development, succession planning, and continuous learning. Support enterprise engineering excellence standards including software craftsmanship, coding standards, architecture reviews, pull request quality, secure coding practices, technical debt management, release readiness, and engineering governance. Champion Shift Left Engineering by embedding quality, security, accessibility, performance, reliability, and compliance practices throughout the software development lifecycle. Drive adoption of AI-assisted Quality Engineering practices including intelligent test generation, autonomous testing, automated test maintenance, defect prediction, release risk analysis, AI-assisted code reviews, and engineering automation. Evaluate emerging AI technologies that improve engineering productivity, software quality, release confidence, developer experience, and customer satisfaction. Support enterprise standards for Responsible AI testing, validation, governance, and quality assurance for AI-enabled products and intelligent software solutions. Support testing practices across unit, integration, API, contract, UI, end-to-end, performance, resilience, security, accessibility, regression, and user acceptance testing. Partner with Platform Engineering and DevOps teams to embed automated quality gates, testing frameworks, compliance validation, security controls, and Quality as Code practices into CI/CD pipelines. Support quality, reliability, performance, observability, and production readiness practices that improve software delivery outcomes. Use engineering metrics, quality indicators, defect trends, test coverage, release quality, and operational performance data to identify improvement opportunities. Perform quality benchmarking, root cause analysis, trend analysis, defect prevention, engineering maturity assessments, and continuous improvement initiatives. Provide guidance to engineering teams and technical leaders on software craftsmanship, engineering excellence, testing strategy, AI-assisted engineering, and modern software development practices. Support engineering Communities of Practice (CoPs) that promote technical standards, knowledge sharing, innovation, mentoring, and continuous improvement. Partner with Product Engineering, Architecture, Platform Engineering, DevOps, Security, Infrastructure, and Product Management to improve engineering maturity. Support software validation and regulatory compliance activities for highly regulated healthcare and life sciences solutions. Continuously evaluate emerging engineering tools, AI platforms, automation technologies, testing frameworks, and software engineering practices that improve software delivery and engineering effectiveness. Support team capacity planning, resource planning, tooling needs, vendor coordination, and quality improvement initiatives. Foster a culture centered on ownership, software craftsmanship, quality, innovation, collaboration, accountability, continuous learning, and engineering excellence. Perform other duties as assigned. Qualifications (Minimum Required): Bachelor's degree in Computer Science, Software Engineering, Information Technology, or related discipline. Equivalent experience will be considered. Strong understanding of modern software engineering, Agile delivery, Engineering Excellence, DevOps, CI/CD, Platform Engineering, and Quality Engineering principles. Deep knowledge of enterprise test automation, software quality practices, engineering governance, software craftsmanship, and engineering maturity frameworks. Experience with automated testing, Quality as Code, engineering automation, Shift Left Engineering, and modern software delivery methodologies. Strong understanding of cloud-native architectures, distributed systems, performance engineering, observability, resilience engineering, and operational excellence. Strong leadership, communication, facilitation, stakeholder management, organizational development, and influencing skills. Demonstrated ability to influence engineering organizations and technical leaders without direct authority. Strong analytical and data-driven decision-making skills focused on continuous improvement and engineering effectiveness. Experience (Minimum Required): 8+ years of progressive experience in Software Engineering, Quality Engineering, DevOps, Platform Engineering, Software Architecture, or related engineering disciplines. 3+ years leading Quality Engineering teams, Engineering Excellence programs, or engineering improvement initiatives. Demonstrated experience supporting Quality Engineering strategies, Engineering Excellence programs, or engineering improvement practices. Proven success implementing test automation across multiple products, platforms, or engineering teams. Experience implementing AI-assisted software engineering and intelligent testing capabilities that improve engineering productivity and software quality. Experience supporting engineering standards, governance processes, software craftsmanship practices, release readiness criteria, and engineering maturity models. Experience implementing DORA Metrics, engineering productivity scorecards, software quality KPIs, and continuous improvement programs. Experience supporting performance engineering, resilience testing, production quality monitoring, and operational excellence initiatives. Experience partnering with Product Engineering, Platform Engineering, DevOps, Architecture, Security, and Data & AI teams. Experience supporting software validation, regulatory compliance, or highly regulated software environments. Demonstrated success supporting improvement initiatives focused on Engineering Excellence, Quality Engineering, or software delivery modernization. Strong experience utilizing engineering metrics, operational analytics, and