<p><strong>About us</strong><br>AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa.</p> <p><strong>About AB InBev Growth Group</strong><br>Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world.</p> <p>In addition to supporting well-known global beer brands like Corona, Budweiser, and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Zé Delivery and TaDa Delivery, and tabletop beer keg PerfectDraft. We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities.</p> <p><strong>About the role:</strong></p> <p>We are looking for a <strong>Technical Product Manager (Data/AI)</strong> to join our <strong>Generative AI & Search</strong> team, playing a critical role at the intersection of business, data science, and software engineering. You will own the strategy, execution, and adoption of GenAI-powered experiences, intelligent agents, and semantic search products used across global markets.</p> <p>This role requires strong product leadership, **a solid technical background to guide and challenge the engineering and data teams**, and the ability to translate complex AI/Search architectures into tangible business value for commercial and customer stakeholders.</p> <p><strong>What you'll do:</strong></p> <p><strong>Drive Strategic Alignment</strong></p> <ul> <li>Partner with global commercial and product stakeholders across LATAM, US, and global markets to enable product understanding, drive adoption, and unlock new Generative AI and Search use cases.</li> <li>Act as a product evangelist—educating stakeholders on LLM/Search capabilities, trade-offs (latency, cost, accuracy/hallucinations), limitations, and product roadmap.</li> <li>Provide regular updates to internal stakeholders and leadership on product adoption, search relevance, agent performance, and business impact.</li> </ul> <p><strong>Plan & Prioritize</strong></p> <ul> <li>Own quarterly product planning in close collaboration with AI/ML Engineers, Data Scientists, Data Engineers, and Software Engineers.</li> <li>Leverage your technical background to balance business value, model/prompt experimentation, search relevance tuning, and platform/infrastructure scalability when defining priorities.</li> <li>Continuously assess team capacity, technical debt, and delivery risk to ensure plans are realistic, achievable, and aligned with broader product and business strategy.</li> </ul> <p><strong>Execute & Deliver</strong></p> <ul> <li>Partner closely with technical teams to execute the quarterly backlog and deliver high-impact GenAI and Search capabilities.</li> <li>Drive the end-to-end delivery of: Conversational AI & Agentic workflows, Semantic & Hybrid Search engines (RAG, vector search), Scalable and low-latency APIs, Evaluation frameworks (LLM-as-a-judge, offline/online evals), and observability dashboards.</li> <li>Define Epics, High-Level Requirements (HLRs), and technical specs, leading refinement sessions with a strong focus on: System architecture, User experience (UX), Search relevance & ranking, and LLM behavior, guardrails, and performance.</li> <li>Lead Agile ceremonies, including daily stand-ups, sprint planning, reviews, and retrospectives, acting as a technical sounding board for the squad.</li> <li>Track delivery and performance metrics, producing sprint summary reports with emphasis on: Team productivity, Search & AI quality metrics (e.g., NDCG, MRR, faithfulness, latency, token cost), and usage/adoption trends.</li> </ul> <p><strong>Engage Stakeholders</strong></p> <ul> <li>Maintain strong relationships with technical, commercial, and senior leadership stakeholders.</li> <li>Present quarterly roadmaps, architectural trade-offs, and progress updates with clarity and confidence.</li> <li>Proactively manage expectations by negotiating scope, timelines, and technical trade-offs across internal teams and customers.</li> </ul> <p><strong>What you'll need:</strong></p> <ul> <li>Strong technical background (e.g., degree or prior hands-on experience in Computer Science, Software Engineering, Data Science, or Systems Architecture) with the ability to constructively guide technical discussions and architecture decisions with engineers and scientists.</li> <li>Proven experience managing data, Search, or AI/ML-driven products, with a strong grasp of Generative AI concepts (LLMs, RAG, Prompt Engineering, Agents, Embeddings) and Information Retrieval / Search (Lexical vs. Vector/Semantic Search, ranking, indexing).</li> <li>Strong understanding of the AI/ML and Search lifecycle, including data pipelines, indexing, context retrieval, evaluation frameworks, deployment, monitoring, and continuous iteration.</li> <li>Ability to translate ambiguous business problems into clear technical product require