Manager, Enterprise AI Product

at  Vanguard

Vanguard is one of the world’s largest and most respected investment management companies, known for its client-centric approach, low-cost investment products, and commitment to long-term, data-driven investment strategies. Our Enterprise AI and Research (EAiR) team is actively working on advancing AI innovation by integrating cutting-edge concepts into the Vanguard AI ecosystem, establishing strategic AI partnerships, and building enterprise-level AI capabilities to empower Vanguard clients with advanced AI research and technology. The team aims to ultimately accelerate critical business solutions with AI capabilities. Some of the team’s areas of research include areas around Agentic AI, Responsible AI, and Cognitive AI Architecture.
Vanguard is one of the world’s largest and most respected investment management companies, known for its client-centric approach, low-cost investment products, and commitment to long-term, data-driven investment strategies. Our Enterprise AI and Research (EAiR) team is actively working on advancing AI innovation by integrating cutting-edge concepts into the Vanguard AI ecosystem, establishing strategic AI partnerships, and building enterprise-level AI capabilities to empower Vanguard clients with advanced AI research and technology. The team aims to ultimately accelerate critical business solutions with AI capabilities. Some of the team’s areas of research include areas around Agentic AI, Responsible AI, and Cognitive AI Architecture.

QUALIFICATIONS:

• Advanced degree (Post Doctorate or PhD in Computer Science, AI, Data Science or related field
• PhD or Master’s degree in a relevant field of study such as Computer Science, Cognitive Science, Mathematics, Statistics, Physics, Electrical & Computer Engineering.
• At least 7+ years of experience in AI/ML research in industry or academic setting.
• Experience with troubleshooting and supporting AI-based or software systems.
• Proven experience managing or mentoring product support teams in a technology-focused environment
• Strong organizational and problem-solving skills to manage multiple priorities and deliver high quality support
• Excellent communication skills to liaise between technical teams and non-technical stakeholders.
• Experience developing and optimizing support workflows, documentation and incident management processes.
• Strong background in architecting and engineering production-grade AI systems, with a focus on scalability and performance.
• Demonstrated success in leading cross-functional AI/ML teams, driving projects from ideation to delivery.
• Familiarity with support tools and platforms like MLOPS, Monitoring solution, JIRA, ServiceNow, or similar systems is a plus.

ROLE OVERVIEW:

We’re looking for a Manager of Enterprise AI Product to oversee the development and maintenance of our advanced Enterprise AI solutions. In this role, you will manage a team of talented AI Engineers, ensuring the seamless operation of AI-powered systems developed by our engineering and research teams. As the manager, you will act as the crucial link between engineering teams, product users, and operational stakeholders, ensuring that all AI solutions perform optimally and meet business needs. If you’re passionate about delivering reliable AI systems and creating smooth support processes, this is the role for you.

CORE RESPONSIBILITIES:

• Product Support Leadership: Lead the product support team, providing guidance, training and mentorship to ensure they effectively manage and resolve technical issues.
• Support Process Optimization: Design and implement scalable product support processes, including issue tracking, resolution workflows, and user feedback loops.
• Solutions Expertise: Gain a deep understanding of AI products and solutions (e.g., Generative AI, Cognitive AI, Agentic AI, transcription systems, language models) to support their operation and performance.
• Stakeholder Collaboration: Act as a bridge between engineering teams and end-users, communicating technical insights, troubleshooting feedback, and product updates.
• Feedback Integration: Work with engineering teams to relay user feedback and performance data, driving continuous improvement of AI systems.
• Incident Management: Oversee incident escalation, ensuring timely resolutions for high-impact issues while communicating progress to key stakeholders.
• Team Development: Hire, manage, and grow a team of skilled product support engineers, fostering a collaborative and solution-focused culture.