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…