VP, AI Quality Software Engineering (Remote)

Broadridge is a company dedicated to empowering others and fostering a collaborative environment. They are seeking a strategic and hands-on VP, AI Quality Software Engineer to lead the application of AI-driven technologies within their Platform Quality Engineering organization, focusing on enhancing software quality and platform reliability.

Responsibilities:

• Define and lead the AI software engineering strategy for the Platform Quality Engineering organization
• Identify opportunities to apply AI, machine learning, and intelligent automation to improve software testing, quality assurance, release confidence, and platform performance
• Partner with senior engineering and business leaders to align AI quality engineering initiatives with enterprise technology priorities and transformation goals
• Establish a roadmap for AI-enabled quality engineering capabilities, including test intelligence, defect prediction, root cause analysis, and quality analytics
• Lead the design, development, and implementation of AI-powered software solutions that enhance quality engineering processes and platform reliability
• Oversee the delivery of scalable tools and platforms that support automated testing, continuous quality validation, and intelligent engineering insights
• Drive the adoption of modern engineering practices across AI development, software delivery, CI/CD, observability, and platform automation
• Ensure AI solutions are integrated effectively into the SDLC and broader platform engineering ecosystem
• Build, lead, and mentor high-performing teams of software engineers, AI engineers, quality engineers, and technical leaders
• Foster a culture of innovation, accountability, collaboration, and continuous improvement
• Attract, develop, and retain top engineering talent with expertise in AI, automation, and quality engineering
• Provide coaching, performance management, and career development to support organizational growth and technical excellence
• Serve as a senior technical leader and thought partner on AI architecture, engineering standards, and platform quality strategy
• Drive best practices for AI model development, testing, deployment, monitoring, and lifecycle management in enterprise environments
• Ensure solutions are designed with a focus on scalability, resilience, security, explainability, and maintainability
• Evaluate and recommend modern tools, frameworks, and platforms to advance AI-enabled software engineering and quality capabilities
• Establish strong governance around AI usage, model quality, data integrity, testing, compliance, and risk management
• Ensure all AI-driven engineering solutions meet enterprise standards for security, privacy, regulatory compliance, and operational excellence
• Define and track KPIs to measure the effectiveness, adoption, and business impact of AI quality engineering initiatives
• Promote disciplined engineering and architecture decision-making while encouraging innovation and experimentation
• Collaborate with platform engineering, product, architecture, infrastructure, data, security, and operations teams to deliver integrated solutions
• Communicate strategy, progress, and outcomes to senior leadership and key stakeholders
• Act as a trusted advisor to engineering leadership on the use of AI to improve software quality, developer productivity, and delivery outcomes

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred
• 12+ years of experience in software engineering, platform engineering, quality engineering, or related technical disciplines
• 5+ years of experience leading large engineering teams and delivering enterprise-scale technology solutions
• Experience building and implementing AI/ML-driven solutions in software engineering, testing, automation, or platform environments
• Strong understanding of SDLC, Agile delivery, DevOps, CI/CD, and modern quality engineering practices
• Deep knowledge of software architecture, cloud-native development, APIs, distributed systems, and platform scalability
• Experience with test automation frameworks, quality engineering tooling, observability, and engineering analytics
• Proven ability to influence senior stakeholders and lead cross-functional transformation initiatives
• Experience applying generative AI, machine learning, NLP, or predictive analytics to software development or quality engineering use cases
• Familiarity with MLOps, model governance, and AI lifecycle management in enterprise settings
• Experience with cloud platforms such as AWS, Azure, or GCP
• Knowledge of data engineering, large-scale data platforms, and intelligent automation technologies
• Financial services or highly regulated industry experience is a plus