VP, AI Engineering and Applied Research

The VP of AI Engineering and Applied Research will support the strategy, development, and delivery of advanced Generative AI capabilities across our product portfolio. This leader will have a critical role driving innovation in AI-powered customer-facing products, ensuring that solutions are production-ready, scalable, cost-optimized, and aligned with the highest standards for quality, safety, and performance.

Partnering closely with the Head of the AI Platform Team, this role will champion the integration of AI capabilities into our platform, enabling seamless adoption across all products. The successful candidate will manage a high-performing team of AI experts, oversee the end-to-end delivery of AI solutions, and collaborate with engineering, product, and operations to ensure measurable business impact.

The person in this role is expected to be in the office at least 2 days a week and potentially more based on business requirements.

Essential Duties and Responsibilities:

Strategic Leadership -

• Support and execute the AI strategy, with a focus on Generative AI solutions for customer-facing products.
• Partner with the AI Platform team to embed reusable, scalable AI capabilities into the core platform.
• Establish best practices for model development, deployment, monitoring, and continuous improvement.
• Grow technology partnerships with key AI technology providers

AI Solution Delivery -

• Work with engineering to deliver of AI solutions from concept to production, ensuring scalability, reliability, and operational readiness.
• Lead advanced tuning, evaluation, and cost optimization strategies for large-scale AI models.
• Ensure model safety, ethical use, and compliance with applicable regulations and policies.
• Support fast-paced innovation initiatives in small collaborative teams with product owners, engineering, product owners, UX and subject matter experts, to bring a working testable solution to customers partners to accelerate new AI-first product development.

Team Development & Collaboration -

• Build, mentor, and retain a team of AI scientists, engineers, and specialists capable of delivering high-impact solutions.
• Foster strong collaboration with engineering, product management, design, and operations teams to ensure AI initiatives meet business and customer needs.
• Promote a culture of experimentation, rapid prototyping, and measurable results.

Operational Excellence -

• Implement robust processes for quality assurance, model governance, and performance monitoring.
• Drive adoption of hyper-scaler AI services and cloud-native solutions to accelerate time-to-market.
• Lead cost management initiatives to optimize AI infrastructure and usage at scale.
• Ensure compliance with AI Governance

Required Qualifications:

• 10+ years of experience in AI, ML, or data science, with at least 5 years in a leadership role.
• Expertise in Generative AI, including LLMs, prompt engineering, RAG, fine-tuning, and evaluation methodologies.
• Proven track record of delivering production-grade AI solutions in customer-facing products especially using LLMs.
• Strong understanding of production software engineering best practices, CI/CD, testing, observability, error handling, and security.
• Experience with cloud-based AI services (AWS, Azure, GCP) and hyper-scaler AI platforms (e.g., Azure OpenAI, Azure AI Services, AWS Bedrock, Google Vertex AI).
• Demonstrated ability to optimize AI model performance and costs for large-scale deployments especially LLMs.
• Exceptional communication and cross-functional collaboration skills.

Preferred Qualifications:

• Experience working in regulated industries or managing sensitive data (e.g. PII, PHI).
• Knowledge of AI governance, responsible AI frameworks, and ethical AI practices.
• Advanced degree (MS/PhD) in Computer Science, AI/ML, engineering or related field.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.