Director, Data & AI [T500-30397]

About CIBC:

CIBC is a leading North American bank, with a history of more than 150 years of living our purpose - to help make your ambition a reality. Client relationships are at the center of our strategy, and our growth is enabled by a highly engaged and connected global team. From digital banking to community impact, we’re proud to drive progress for our clients and our communities. Recognized for our culture, award-winning innovation and community investment, CIBC continues to evolve by putting people and progress at the centre of everything we do.

About CIBC India:

CIBC India is a technology and operations hub in Hyderabad, where you’ll be part of our highly engaged and global team, and play a central role in supporting our growth. Whether you’re driving innovation in digital banking or streamlining client onboarding, you’ll be part of a culture recognized for excellence and investment in people. At CIBC India, people and progress are at the center of what we do: you’ll develop skills, collaborate with industry leaders, and see your ideas realized in a culture that values progress and belonging. We provide cutting-edge resources, ongoing learning, and a supportive environment where people come first. If you’re ready to create meaningful change and build your future, CIBC India is where your ambition meets opportunity.

What CIBC India Offers:

At CIBC India, your goals are a priority. We start with your strengths and ambitions and strive to create opportunities to tap into your potential. We aspire to give you a career that goes well beyond your compensation.

We work to recognize you in meaningful, personalized ways including competitive fixed pay, performance-based incentive programs, a family-first benefits program, employer contributions for your retirement, attractive time off and leave offerings, wellbeing support, and MomentMakers, our social, points-based recognition program.

Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients worldwide

We cultivate a culture where you can express your ambition through initiatives like Purpose Day, a paid day off dedicated for you to use to invest in your growth and development.

What You’ll Be Doing (position summary):

This role is accountable for shaping, delivering and evolving enterprise-grade data, data product and AI capabilities that support strategic business priorities. The incumbent leads the design, implementation and continuous improvement of scalable data engineering foundations, reusable data products and advanced AI solutions across business-aligned teams. The role combines leadership in data engineering, data product development, advanced analytics, machine learning and GenAI to ensure trusted, high-quality, secure and scalable data products power analytics and AI use cases across the organization. The incumbent also leads, manages and mentors teams while driving cross-functional stakeholder engagement, delivery execution and change management in support of enterprise data and AI initiatives.

How You’ll Succeed (responsibilities):

Design and Development:

• Champion the use of data, data products, advanced analytics and AI to solve business problems in order to deliver scalable business-aligned solutions.
• Define, create and implement reusable data products in order to support reporting, analytics, operational decisioning, machine learning and GenAI use cases.
• Lead the implementation and evaluation of AI solutions in order to create, validate, deploy and monitor traditional AI/ML and GenAI capabilities.
• Provide end-to-end solution ownership from scoping and architecture through development, deployment, monitoring and continuous improvement in order to deliver enterprise-grade outcomes.

Strategic Planning:

• Support data product strategy and execution in order to align reusable enterprise data assets to business priorities.
• Implement and evolve data engineering standards, product-oriented delivery patterns, reference architectures and reusable frameworks in order to improve consistency and scalability across teams.
• Establish data contracts, schema evolution practices, backward compatibility standards and product ownership principles in order to ensure trusted and reusable data foundations.
• Drive scalable ingestion, transformation and serving patterns in order to enable structured and unstructured data …