Jobs at Syngenta Group

Leads the R&D Activity Product-Oriented Delivery portfolio, setting product vision, roadmaps, priorities, investment decisions, and success metrics. Oversees digital products supporting laboratory and field R&D, including experimentation, trials, sensors, imaging, and geospatial data. Leads cross-functional stakeholders and Product Managers while managing delivery governance, data governance, security, compliance, vendors, budgets, risks, and operational excellence. Ensures scalable, secure, high-quality products that deliver measurable business and user outcomes.

Lead the vision, strategy, roadmap, delivery, adoption, and value realization of R&D digital products supporting analytics, forecasting, optimization, planning, and AI-enabled decision-making. Manage prioritization, budgets, risks, dependencies, governance, stakeholder alignment, product outcomes, and continuous improvement. Partner across R&D, data, technology, security, and architecture teams while coaching Product Managers and maintaining executive visibility.

Leads vegetable crop product-placement trials from planning through data collection, analysis, visualization, and market recommendations. Coordinates off-station trials with growers, designs and evaluates trials, manages contracts and trial networks, and presents product advancement proposals. Builds relationships with growers, dealers, processors, breeding, marketing, and commercial teams while developing regional market and crop expertise. The role requires substantial seasonal travel, flexible hours, and occasional overnight or extended work.

Lead the technical direction of AWS and GCP cloud foundations, including Terraform, infrastructure as code, networking, governance, security, FinOps, reliability, and incident response. Partner with engineering, product, and scientific teams; conduct architecture reviews; establish standards; guide cloud design decisions; and mentor engineers. The role also requires stakeholder management with hyperscalers, technical leadership without direct authority, and rigorous use of AI-assisted engineering.

Develop and validate machine-learning and predictive models for Crop Protection R&D using complex scientific, laboratory, environmental, and field-trial data. Collaborate with multidisciplinary scientists and software teams, guide experimental design, support data strategy, communicate insights to technical and non-technical stakeholders, track modelling impact, document methods, and mentor junior data professionals.

Develop predictive and statistical models for Crop Protection R&D using experimental and heterogeneous datasets. Collaborate with scientific experts, support experimental design and field trials, and prototype GenAI applications including RAG, knowledge extraction, knowledge graphs, and agentic workflows. Evaluate and govern AI tools, contribute to responsible AI and data governance practices, and work with engineering teams to deploy analytical solutions.

Lead design and implementation of AI-powered decision support and planning systems for R&D. Drive backend engineering (Python/Java), architecture, document ingestion, embeddings-based retrieval, testing, security, and scalability. Mentor engineers, collaborate across product and science teams, and maintain technical documentation and compliance.

Lead EU regulatory mammalian toxicology strategies for crop protection products. Manage toxicology data and submissions, interpret scientific risk assessments, liaise with authorities (EFSA, ECHA), train and mentor staff, and represent Syngenta in industry working groups.

Lead platform and infrastructure initiatives, manage engineering teams and vendors, own incident/SLA processes, delivery across workstreams, budget and SoW oversight, define KPIs, drive modernization and AI-assisted engineering practices, and communicate operational status to stakeholders.

Lead AI enablement by designing and delivering scalable AI infrastructure, MLOps, model serving, vector DBs, HPC/GPU scheduling, and AI safety. Drive roadmaps, metrics, POCs, cross-team collaboration, and build/mentor a high-performing ML engineering team.

Lead design, deployment and optimization of HPC clusters, GPUs, storage, job scheduling and Kubernetes-native orchestration for scientific workloads. Partner with scientists and engineers, set standards for security, monitoring and disaster recovery, manage vendor strategy and budgets, mentor engineers, and produce documentation and training to enable reliable compute for R&D.

Lead design and delivery of scalable backend and frontend solutions for screening operations and logistics. Own end-to-end systems, apply AI-assisted engineering, mentor junior engineers, drive CI/CD and DevOps practices, optimize performance, and collaborate with product and scientific teams to translate complex workflows into reliable production services.

Lead governance and adoption of Syngenta's global HSE learning ecosystem. Manage digital learning platforms, oversee competence records and content lifecycle, deliver learning and competence reporting, build a global training network, drive engagement and CPD, and liaise with platform owners to improve learner experience.

Analyze historical biological and field-trial data to uncover patterns affecting product performance, build and validate ML/deep learning models for crop protection outcomes, support R&D decision-making, design field trials with technical managers, integrate models with IT/software, and communicate insights to technical and non-technical stakeholders.

Support EU regulatory toxicology for crop protection products: manage toxicology data and projects, prepare and review regulatory submission sections, liaise with risk assessment teams and authorities (EFSA, ECHA), and contribute to strategy, training, and industry working groups to ensure safety and compliance.