AI Lead

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do?

The key purpose of an AI Tech lead is to be responsible for designing, architecting, and delivering advanced analytics and Generative AI solutions that create measurable business value across the organization. The role combines hands-on delivery expertise with technical leadership, ensuring that AI and analytics solutions are scalable, secure, cost-effective, and aligned with enterprise architecture standards.

The position plays a critical role in establishing technical patterns, reference architectures, and implementation frameworks that enable the rapid development and deployment of AI solutions while maintaining governance, responsible AI principles, and data integrity. The role collaborates closely with business stakeholders, engineering teams, data professionals, and enterprise architecture functions to accelerate AI adoption and value realization across the business.

Key Roles and Responsibilities:

AI Architecture & Technical Leadership

• Design scalable AI, machine learning, and Generative AI solution architectures aligned to enterprise standards.
• Establish and maintain reference architectures, technical patterns, reusable components, and implementation frameworks.
• Drive technology selection and provide guidance on appropriate AI approaches, including machine learning, Generative AI, Retrieval-Augmented Generation (RAG), agentic systems, and analytics solutions.
• Present solution architectures and technical recommendations to architecture governance forums and review boards.
• Ensure solutions incorporate security, privacy, compliance, responsible AI, and cost management requirements from inception.

AI & Analytics Solution Delivery

• Design, develop, and implement advanced analytics, machine learning, and Generative AI solutions to address business challenges.
• Lead the end-to-end delivery lifecycle including problem framing, data preparation, model development, validation, deployment, monitoring, and continuous improvement.
• Deliver predictive, prescriptive, and descriptive analytics solutions that support business decision-making.
• Ensure production-ready development practices including testing, performance optimisation, documentation, and deployment automation.
• Collaborate with technical and business stakeholders to prioritise and execute high-value use cases.

Data & Platform Enablement

• Partner with data engineering and platform teams to ensure reliable, scalable, and trusted data foundations.
• Support the evolution of AI and analytics platforms through best practices, standards, and technical governance.
• Contribute to technical roadmaps and long-term capability development strategies.
• Evaluate emerging technologies and industry trends to identify opportunities for innovation and efficiency.

Capability Development & Enablement

• Mentor analysts, data scientists, AI engineers, and other technical team members.
• Support capability building through technical coaching, knowledge sharing, and community activities.
• Promote responsible AI practices and increase AI literacy across the organisation.
• Develop training materials, implementation guides, and best-practice documentation.

Stakeholder Management & Collaboration

• Partner with business stakeholders to identify opportunities for AI and analytics-driven value creation.
• Translate business requirements into scalable technical solutions.
• Manage stakeholder expectations and communicate technical concepts effectively to both technical and non-technical audiences.
• Collaborate with global and local teams to align solutions with enterprise strategies and standards.

Work Environment

• This role operates within a cross-functional analytics and AI capability supporting multiple business functions and markets. The position requires close collaboration with business leaders, product owners, data engineers, analysts, architects, and enterprise technology teams.
• The role serves as a bridge between business strategy and technical implementation, balancing hands-on solution delivery with architecture responsibilities. Regular engagement with governance forums, leadership teams, and technology stakeholders is required to ensure alignment, scalability, and sustainable value delivery.
• The operating environment is dynamic and innovation-focused, requiring agility, continuous learning, and the ability to manage multiple priorities simultaneously.

Key Attributes and Competencies:

Minimum Requirements:

• Bachelor's Degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Information Systems, or a related quantitative discipline.
• 5+ years of experience in Data Science, Machine Learning, Advanced Analytics, or AI-related roles.
• Demonstrated experience designing and delivering AI or advanced analytics solutions in enterprise environments.
• Experience delivering Generative AI applications and solutions.
• Experience working with cloud-based data and AI platforms.
• Experience presenting technical solutions to architecture, governance, or leadership forums.

Additional Information:

• Band: VI

AB InBev is an equal opportunity employer, and all appointments will be made in-line with AB InBev employment equity plan and talent requirements. We are a company that promotes gender equality. Internal applicants require Line manager approval. Please note that only short-listed applicants will be contacted. Management reserves the right to use additional/relevant information as criteria for short-listing.