Senior Director, AI Engineering

Cornerstone provides an AI-powered Talent Experience Platform enabling unified content discovery, knowledge management, and personalized learning experiences across the career journey. Our platform is trusted globally by leading enterprises and government organizations to address complex challenges in discovery, curation, and recommendation across diverse knowledge sources.

As we accelerate investment in transformative AI product initiatives, Cornerstone seeks a Senior Director of AI Engineering to architect, lead, and scale our next-generation AI capabilities. This strategic leader will drive the development and delivery of innovative AI solutions that redefine how millions of users learn, grow, and perform.

The Role

The Senior Director, AI Engineering, will own end-to-end technical strategy, execution, and organizational leadership for our AI engineering division. In collaboration with Product, Data Science, and Engineering leadership, you will help define and realize our AI vision-overseeing multiple teams responsible for AI-driven features, recommendation systems, generative AI, and actionable insights. You will set standards, ensure operational excellence, drive cross-functional adoption, and build a world-class engineering culture.

Responsibilities

Strategic & Technical Leadership

• Set and execute the strategic technical direction for AI engineering across all product lines, ensuring alignment with business objectives and product vision.
• Architect foundational AI platform components-recommendation systems, generative AI, ML infrastructure, and data analytics-to support scalability, security, and extensibility.
• Lead adoption of advanced machine learning methodologies, MLOps best practices, and production-grade AI reliability.
• Oversee platform-wide architecture decisions, including CI/CD pipelines, cloud-native deployments, and automation supporting the full ML lifecycle.
• Champion rapid experimentation and data-driven iteration, driving continuous improvement in model performance, user engagement, and measurable outcomes.

• Own the execution and delivery of AI/ML initiatives across multiple engineering teams and products, ensuring quality, predictability, and impact.
• Define and monitor key metrics for system reliability, customer value, and product success.
• Partner with Product, Data Science, and Customer teams to ensure AI solutions meet operational, compliance, and stakeholder requirements.
• Serve as the technical spokesperson for AI initiatives, interfacing with executive leadership, clients, and external partners.

• Build, mentor, and scale high-performing teams of engineering managers, software engineers, and ML specialists in a diverse, autonomous environment.
• Foster an inclusive culture of innovation, collaboration, and operational excellence.
• Develop organizational capabilities for talent acquisition, development, and retention as the AI portfolio evolves.
• Lead organizational change, championing Agile and Lean methodologies and driving cross-functional alignment.

• Programming & Data: Python, Java/Kotlin, advanced data and visualization libraries.
• Backend & Data: RESTful APIs, distributed systems, analytical databases.
• AI/ML: PyTorch, TensorFlow, Hugging Face, OpenAI APIs.
• ML Pipelines & MLOps: Apache Airflow, Kubeflow, Ray (or equivalent).
• Cloud & DevOps: CI/CD, cloud deployment, monitoring, infrastructure automation.
• Development Practices: Scaled Agile/Lean, enterprise software development.

• Bachelor's or Master's degree in Computer Science or related field; PhD preferred.
• 15+ years of progressive experience designing and building scalable, mission-critical systems at enterprise scale.
• 10+ years of experience driving AI/ML strategy and delivery, including NLP, generative AI, and advanced recommendation systems.
• 8+ years in engineering leadership roles, including direct management of managers and multi-team organizations in high-growth environments.
• Deep expertise in ML algorithms (classical and deep learning), frameworks, system architecture, and operational best practices.
• Proven track record with high-availability architectures, security, performance, and compliance in cloud environments.
• Exceptional communication, executive presence, and stakeholder management skills.
• Deep commitment to customer-centric innovation and product excellence.