VP, AI Software Engineering (Hybrid - Flexible Options)

At Broadridge, we've built a culture where the highest goal is to empower others to accomplish more. If you're passionate about developing your career, while helping others along the way, come join the Broadridge team.

We are seeking a strategic and hands-on VP, AI Software Engineer to lead the application of AI-driven technologies within our Platform Quality Engineering organization. This leader will define and execute the engineering strategy for leveraging artificial intelligence and automation to improve software quality, accelerate delivery, and enhance platform reliability across the enterprise.

This role will sit at the intersection of AI engineering, software development, test automation, platform quality, and enterprise transformation. The ideal candidate will bring a strong foundation in modern software engineering, quality engineering, and applied AI/ML, along with a demonstrated ability to lead high-performing teams and deliver scalable, secure, and resilient solutions. This position requires both strategic vision and technical depth, with responsibility for advancing AI-enabled quality engineering capabilities that improve efficiency, reduce risk, and drive innovation.

Key Responsibilities

Strategic Leadership

• 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.

• 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.