Jobs at AB InBev

Leads two engineering teams as a people manager and delivery coordinator. Responsibilities include performance management, hiring support, technical delivery, enterprise integrations, quality and operational discipline, partner UAT, incident readiness, and cross-team dependency resolution. The role requires strong Java and Spring experience, production-scale microservices expertise, customer-facing communication, Agile delivery, and hands-on support for complex integration and production issues.

Develop and deploy advanced machine learning and deep learning solutions for portfolio optimization, recommendations, personalization, forecasting, segmentation, and insights. Architect scalable data workflows using Azure, Databricks, Spark, Python, and PySpark. Collaborate with engineering, product, and business teams to deliver production-ready models, promote modern ML practices, and mentor junior and mid-level data scientists.

Own the strategy, roadmap, execution, and adoption of GenAI-powered experiences, intelligent agents, and semantic search products. Partner with commercial stakeholders, engineers, and data scientists to prioritize capabilities, define technical requirements, lead Agile delivery, and manage search relevance, AI quality, latency, cost, observability, and adoption metrics. Translate complex AI and search architectures into business value while guiding technical decisions and stakeholder alignment across global markets.

Own the design and delivery of canonical data models, master-data solutions, entity resolution, data-quality controls, lineage, and ontology-aligned datasets. Profile source systems, define entities and relationships, create Databricks datasets using Python, SQL, and Spark, and support data scientists and analysts. Contribute to code, testing, documentation, lifecycle management, and governance while mentoring engineers and collaborating with business stakeholders.

Design, deploy, and optimize multi-agent AI systems, RAG pipelines, and low-latency model-serving infrastructure. Build observability and evaluation frameworks, integrate structured and unstructured data, and implement AI security controls such as guardrails and prompt-injection prevention. Collaborate on distributed systems, GPU utilization, caching, CI/CD, and cloud-native ML deployments using Kubernetes and public-cloud platforms.

Lead the global data product strategy for BEES Growth and Logistics. Manage multidisciplinary data teams, prioritize agile roadmaps, and develop scalable products including prioritization algorithms, visit models, databases, and operational KPIs. Translate business needs into technical solutions, ensure data pipeline quality and governance, monitor product and commercial performance, and collaborate with senior leaders, country teams, commercial operations, technology teams, and external partners.

Own FinOps and data initiatives focused on optimizing Databricks workloads, pipelines, clusters, storage, and cloud costs. Build executive dashboards, monitor spending, detect anomalies, establish governance, and improve showback, chargeback, forecasting, and unit economics. Partner with engineering, finance, product, cloud, and operations teams to guide cost-efficient architecture and ROI-based decisions.

Own the strategy, requirements, roadmap, and delivery of data products supporting BNPL and digital payments across global markets. Collaborate with analytics, engineering, data science, commercial, and product teams to define data workflows, KPIs, governance standards, and AI-enabled solutions. Lead Agile planning ceremonies, communicate product outcomes to stakeholders, and translate complex data concepts into actionable business recommendations.

Leads global category management initiative execution across markets and key accounts. Translates global strategies into actionable plans, coordinates tools and capabilities, monitors implementation, manages risks, and drives corrective actions. Partners with Sales, Marketing, Commercial Strategy, and Key Account teams across geographies. Develops executive presentations, business cases, deployment plans, training, workshops, and best-practice programs while improving processes and organizational effectiveness.

Owns global third-party invoicing and revenue recognition for BEES. Responsibilities include triggering monthly invoicing, reconciling commercial and financial revenue views in Cognos, monitoring partner and country invoicing status, escalating delays and blockers, coordinating accounting operations, and providing visibility into intercompany charges. The role standardizes centralized invoicing processes while accommodating local requirements across partners and countries.

Own a Sales Insights pillar supporting commercial strategy through metrics, dashboards, performance visibility, and actionable analysis. Translate business needs into insights, ensure dashboard reliability and adoption, and identify opportunities for AI and automation. Partner with Commercial, Product, Data, and Analytics teams to align business objectives with data initiatives.

Analyze performance across global expansion markets, identify growth opportunities and gaps, and recommend actions. Own KPI frameworks, dashboards, reporting routines, and measurement methodologies while validating data quality. Partner with Commercial and Data teams to define requirements, prioritize analytical solutions, and deliver data products. Support forecasting, planning, and target setting, translating complex analyses into executive-ready insights and recommendations.

Lead the strategic roadmap and implementation of enterprise data platforms, including Lakehouse, ETL, streaming, and MDM capabilities. The role guides architecture, modernization, scalability, governance, reliability, data quality, and production readiness across multiple engineering teams. Responsibilities include mentoring engineers, defining standards, evaluating architectural trade-offs, driving platform optimization, and contributing hands-on to critical implementations in highly scalable, mission-critical environments.

Provide remote night-shift support for production services by monitoring systems, improving observability, automating processes, managing releases, mitigating incidents, conducting root cause analysis, and maintaining runbooks. Collaborate with infrastructure, security, operations, and development teams to build scalable and resilient systems. Define SLOs and error budgets, support capacity planning and access management, manage third-party tickets, and improve change management and support processes.

Build and operate backend services for a web analytics and AI portal. Responsibilities include designing APIs, authentication, multi-tenant access control, analytical data read paths, performance optimization, observability, reliability, incident response, and safe deployments. The role also delivers full-stack features with TypeScript, integrates AI services, writes design documents, reviews code, and raises engineering standards. This is a hands-on Staff-level position requiring distributed systems, production operations, scalability, and performance expertise.

Lead the architecture and hands-on implementation of high-performance, data-intensive web applications on Microsoft Azure. Design services, APIs, data models, integrations, security, observability, and distributed systems while writing critical production code. Optimize SQL, caching, search, pagination, aggregation, latency, throughput, and cost. Establish engineering standards for testing, CI/CD, containers, Kubernetes, and infrastructure as code, and collaborate with data platform teams to deliver scalable dashboards and personalization capabilities.

Intermediate QA Engineer responsible for testing backend services, APIs, integrations, internal tools, and platform capabilities. Duties include designing functional, integration, regression, exploratory, and automated API tests; validating contracts, errors, logs, and data consistency; tracking defects; monitoring test results; assessing risks; supporting agile delivery, root-cause analysis, and continuous QA improvement; and mentoring junior QA team members.

Leads AB InBev’s Australia business with full P&L accountability, commercial strategy ownership, partner management, route-to-market execution, brand growth, profitability, and organizational capability building. The role manages senior relationships with distributors and other partners, translates company ambitions into market choices, delivers volume and margin commitments, and leads teams and governance across a complex partner-dependent market.

Develop and maintain backend features for a global B2B commerce platform. Build testing and release tooling, improve automation and DevOps processes, advocate for user experience, establish quality strategies, and deliver scalable solutions. The role requires strong Java backend development, RESTful services, microservices, Spring, software testing, DevOps tools, Agile experience, and advanced English communication.

Lead complex technical product initiatives across B2B, direct-to-consumer, and platform capabilities. Responsibilities include shaping roadmaps, assessing technical feasibility, writing product requirements and integration specifications, designing platform capabilities with engineering and architecture teams, coordinating global stakeholders, and measuring reliability, performance, and user impact. The role requires technical understanding of scalable architectures, cloud infrastructure, APIs, data analysis with SQL, and cross-functional leadership.