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# Global AI & Data Technology Lead

- **Company:** Bayer AG
- **Location:** St. Louis, MO, United States
- **Experience:** Expert
- **Salary:** $151,120.0 - $226,680.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Software Applications, Cloud Engineering, Data Architecture, Information Engineering, Data Governance, Decision Support Systems, DevOps, Machine Learning, SAP (Applications), Software Engineering, Systems Integration, Technical Data Management Systems, Enterprise Data Management, Cloud Platform System, Generative AI, Data Analytics, Enterprise Integration, Data Management, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** October 2, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3414911859&tx=KK8383FFR&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 10+ years of experience in data, analytics, AI, software engineering, solution architecture, or related technical leadership roles;
 * At least 4 years of people leadership experience, including coaching, mentoring, and developing technical talent;
 * Proven experience delivering enterprise-scale data and digital solutions in complex, matrixed environments;
 * Strong understanding of cloud architecture, data engineering, and modern analytics platforms;
 * Experience with AI/ML, Generative AI, and intelligent automation initiatives, including design, implementation, and operationalization;
 * Ability to influence stakeholders and effectively bridge business strategy with technology execution;
 * Strong communication, leadership, and mentoring skills, with a track record of collaborating across diverse teams and geographies., * Experience with AWS, Databricks, and cloud-native solution development;
 * Background in data engineering, API integration, and pipeline architecture;
 * Experience with AI/ML, GenAI, and MLOps practices, including monitoring and lifecycle management of models;
 * Exposure to supply chain, manufacturing, or operational analytics use cases;
 * Experience with SAP, CSW, and other enterprise platform integrations;
 * Familiarity with data governance and responsible AI frameworks;
 * Experience in agile product delivery and digital product management, including iterative delivery and stakeholder engagement.

In this role, success is reflected in increased adoption of AI-powered decision support and automation; timely completion of data-driven project milestones; modern, scalable, and reliable data architecture; faster delivery of analytics and digital solutions; stronger technical capabilities across the DPE team; and measurable business impact through improved efficiency, decision quality, and operational performance.

## Description

The primary responsibilities of this role, Global AI & Data Technology Lead - Global Vegetable Seeds Product Supply, are to:

 * Define and execute the AI, data, and analytics technology roadmap, ensuring alignment with Product Supply strategy and enterprise digital direction;
 * Identify, prioritize, and implement business use cases best suited for AI-enabled solutions, focusing on opportunities with clear value, feasibility, and scalability;
 * Lead a team of data science and data analytics resources, establishing best practices, overseeing project resource allocation, and aligning work with business priorities;
 * Provide technical leadership across data platforms, cloud environments, integrations, and internally developed applications, ensuring solutions are robust, secure, and scalable;
 * Guide architecture and solution design across AWS, Databricks, enterprise data platforms, and broader cloud ecosystems to enable modern, cloud-native capabilities;
 * Establish best practices for data engineering, AI development, DevOps, governance, and solution scalability, embedding quality, reliability, and reusability into all deliveries;
 * Lead the modernization of data pipelines, data products, and self-service analytics capabilities, enabling faster, more reliable access to high-quality data;
 * Mentor and upskill analytics, engineering, and application development resources, building stronger technical capabilities across the broader DPE (Data, Platforms & Engineering) team;
 * Partner with business leaders to translate opportunities and challenges into scalable digital and AI solutions that support supply chain, manufacturing, and operational goals;
 * Evaluate emerging technologies and drive innovation across supply chain and operational processes, ensuring responsible adoption of AI, data, and automation;
 * Develop reusable data products and AI-enabled business capabilities that can be leveraged across use cases and functions to accelerate future delivery;
 * Measure and communicate the business impact of AI solutions, including improved efficiency, decision quality, and operational performance, and use these insights to guide future investments.