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?
AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The centre leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics.
Do You Dream Big?
We Need You.
Job Title: Senior Manager, Gen AI Martech
Reporting to: Director
PURPOSE OF ROLE
To program manage the delivery, scaling and adoption of enterprise AI intelligence products that can translate business requirements into trusted insights and actionable recommendations for business leaders. The role bridges stakeholders, product, data, analytics, and technology teams to define use cases, align roadmaps, implement features, and ensure the products create measurable business impact.
KEY TASKS AND ACCOUNTABILITIES
- Own end-to-end program management for conversational AI intelligence products, from intake and prioritization through delivery, launch, adoption, and performance tracking.
- Lead a high performance team to advance on the strategy of build, buy and integrate agents to build world class AI intelligence products
- Partner with business stakeholders to capture requirements, clarify success metrics, translate needs into product-ready user stories, and manage trade-offs across scope, timing, and impact.
- Collaborate closely with product managers, data scientists, data engineers, UX, analytics, and technology teams to implement features that are accurate, usable, secure, and scalable.
- Build and maintain delivery roadmaps, sprint/release plans, dependency maps, risk logs, decision records, and executive-ready status reporting.
- Drive adoption of AI products through stakeholder enablement, launch communications, training materials, feedback loops, and operating routines.
- Define and monitor product health metrics, including usage, answer quality, adoption, business value, model/data quality issues, and stakeholder satisfaction.
- Establish governance routines for responsible AI delivery, including data readiness, privacy, access controls, human-in-the-loop review, quality assurance, and escalation paths.
- Identify high-value use cases, evaluate feasibility with product and data teams, and sequence delivery to maximize business impact while managing complexity.
- Serve as the operating bridge between business, product, data, and technology teams, removing blockers and ensuring decisions are made at the right level.
- Support alignment between local, zone, and global AI strategies so conversational AI products can be reused, scaled, and continuously improved.
3. BUSINESS ENVIRONMENT
Main Characteristics:
This role operates in a fast-moving AI product environment where business teams need practical intelligence products that improve decision-making, automate insight access, and create repeatable ways of working. The role requires strong program discipline, stakeholder management, product fluency, and enough technical understanding to partner effectively with data and engineering teams.
Geographical Scope: Global / Zone scope depending on product portfolio and deployment roadmap.
Key Dimensions and Contacts:
Business stakeholders and functional leaders who sponsor use cases and define adoption needs.
Product leaders and product managers responsible for roadmap, prioritization, user experience, and release planning.
Data science, data engineering, analytics engineering, platform, architecture, security, and privacy teams responsible for implementation and governance.
Analytics, insights, commercial, revenue management, marketing, operations, and transformation teams as end users and adoption partners.
External technology or implementation partners where needed to accelerate delivery while protecting product ownership and avoiding vendor lock-in.
QUALIFICATIONS, EXPERIENCE, SKILLS
Please list the following requirements
Level of educational attainment required:
- BS degree in Engineering, Computer Science, Data/Analytics, Business, or related field. MBA, Masters degree, product management certification, or agile/program management certification preferred.
Previous work experience required:
- 6+ years of relevant business, product, analytics, technology, or consulting experience, including experience managing cross-functional delivery programs. Experience with AI, GenAI, conversational products, analytics products, data platforms, or digital transformation strongly preferred. CPG or enterprise-scale technology experience is a plus.
IT skills required:
- Strong understanding of product delivery, agile ways of working, analytics/data products, conversational AI concepts, prompt and response-quality evaluation, data pipelines, dashboards, user acceptance testing, release management, and adoption tracking.
- Ability to work with product, data science, data engineering, UX, architecture, security, and privacy teams without needing to be the technical implementer.
Other skills required:
- Program management: delivery planning, risk and dependency management, stakeholder alignment, executive communication, prioritization, and change control.
- Business analysis: ability to translate ambiguous business needs into requirements, user journeys, acceptance criteria, success metrics, and product backlog items.
- Product mindset: customer empathy, adoption focus, iterative delivery, value measurement, and continuous improvement.
- AI delivery discipline: understanding of responsible AI practices, data readiness, answer-quality evaluation, human review, governance, and model/product performance monitoring.
- Communication: exceptional written, verbal, and presentation skills, with the ability to explain technical topics clearly to business audiences and business trade-offs clearly to technical teams.
- Collaboration: strong relationship-building, influencing, negotiation, and facilitation skills across senior stakeholders and execution teams.
- Operating style: comfortable with ambiguity, able to create structure quickly, and resilient in a dynamic environment with evolving AI capabilities and business priorities.
COMPETENCIES
Functional area
Goal
Competencies
Operational stewardship
Optimizing business operations
- Driving agility
- Ensuring security and resilience
- Leveraging ecosystems
IT leadership
Anticipating and aligning with business needs
- Fusing business and technology strategy
- Developing talent
- Designing the Analytics operating model
Entrepreneurship
Delivering competitive advantage
- Forward-thinking
- Continuous improvement mindset
- Financial acumen
And above all of this, an undying love for beer!
We dream big to create future with more cheers.