Software Engineering Manager AI

Syngenta is a global leader in agricultural innovation, operating in more than 90 countries. Our mission is to empower farmers with advanced technologies and practices that enable them to feed a growing global population while preserving the planet for future generations. Our pioneering scientific discoveries deliver superior benefits to farmers and society on an unprecedented scale. Guided by our Sustainability Priorities, we continuously develop technologies and solutions that help growers cultivate healthier crops in revitalized soils while maximizing productivity. Syngenta Crop Protection is headquartered in Basel, Switzerland, while Syngenta Seeds is headquartered in the United States. Learn more about our stories and follow our work on LinkedIn , Instagram & X .

Job Description
Within IT & Digital, we aim to transform agriculture through Artificial Intelligence, digital technology, and data. With a user-centered approach, we develop and maintain AI solutions that optimize our global seeds business and create value for growers. We are looking for a Software Engineering Manager – AI to join our Vegetable Seeds business and lead the development of products leveraging Machine Learning, Generative AI, and Advanced Analytics. You will connect complex supply chain data with digital solutions and work closely with the Head of IT & Digital and Vegetable Seeds leadership to embed AI into global operations-from production and processing to quality and logistics. This role combines people management, technical leadership, and hands‑on development, with equal importance across these areas. You will take ownership of the platform’s architecture and AWS environment, lead a team, and contribute directly to the codebase. A key priority will be to build team autonomy and lead knowledge transfer from partners, consolidating internal ownership of the platform. With a global scope and an active roadmap, this is an opportunity to build and scale Data and AI capabilities within a valuable business division‑shaping technical decisions, developing talent, and expanding solutions to new crops and regions. Responsibilities Develop and execute the engineering strategy for AI products, aligned with global Vegetable Seeds objectives; Lead end-to-end application development, ensuring reliability, security, ethical AI standards, and a user‑centered experience; Take ownership of the platform’s AWS architecture and infrastructure, working with Cloud, Infrastructure, and Security specialists to guide its evolution; Contribute through coding, code reviews, testing, and technical troubleshooting, maintaining direct involvement in delivery; Collaborate with AI Product Managers, Data Leads, Data Engineering, and the global Data organization to ensure high‑quality pipelines and AI interfaces that meet user needs; Identify deployment opportunities across the 85 countries where Vegetable Seeds operates, promoting the reuse of models, components, and best practices; Lead, support, and develop engineers by providing feedback and mentoring, increasing team autonomy and fostering continuous learning in AI; Manage initiative budgets and timelines, considering GPU resources, cloud computing, and high‑performance data processing; Monitor AI trends, such as Computer Vision for seed quality and Retrieval‑Augmented Generation (RAG) for internal knowledge management, assessing their potential to create value; Lead knowledge transfer from partners to the internal team, including architecture, documentation, and the capability to maintain and evolve solutions; Build relationships with Product, business, AI Foundry, and global technology teams to resolve dependencies, communicate risks, and negotiate priorities. Qualifications Required 10+ years of product engineering experience, including at least 3–5 years specifically focused on implementing AI/ML at enterprise scale; Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence/Machine Learning, Engineering, or a related field; Hands‑on experience with AI frameworks such as PyTorch and TensorFlow; cloud AI services such as Databricks and AWS; and modern software architecture; Practical AWS knowledge and current ability to code, review, test, and debug, contributing directly to the development and operation of solutions; Proven ability to apply AI to real‑world supply chain, quality, or production challenges within a global manufacturing or agricultural environment; Strong experience leading high‑performing, distributed teams using agile methodologies to deliver AI value iteratively; Previous people‑management experience, including responsibility for feedback, performance, and engineers’ development; consistent experience leading small teams is relevant to this role; Ability to build and develop technical teams, guiding professionals with different levels of experience and autonomy; Experience managing change in large organizations and aligning technology initia