Lead AI Solutions Architect

Company Description

Syngenta Group
, a global leader in agricultural technology and innovation, employs 60,000 people across more than 100 countries to transform agriculture through tailor‑made solutions for farmers, society, and our planet. Our diverse portfolio encompasses seeds, crop protection, nutrition products, agronomic solutions, and digital services, all designed to help farmers produce healthy food, feed, fiber, and fuel while conserving natural resources and protecting the environment.

Our mission is to address critical challenges such as climate change and food security through sustainable practices and cutting‑edge solutions, while safeguarding the planet’s resources.

We are seeking a Lead AI Solution Architect / Staff AI Engineer to serve as the primary technical catalyst for AI within our business domains. Embedded directly within the business from the Enterprise Data Office Solution Architecture team, you will be the domain’s trusted authority for identifying, designing, and accelerating the delivery of production‑grade ML, GenAI, and Agentic AI solutions.

Your mission is to bridge the gap between high‑level AI strategy and tangible business impact. You will lead the ideation and engineering of high‑value AI products ensuring they are scalable, secure, and resilient while utilizing real‑world delivery experience to refine our internal AI platforms and engineering standards. This is a hands‑on leadership role requiring deep expertise in AWS and Databricks, modern cloud data architectures, and the ability to influence senior stakeholders through clear technical communication.

• Act as the primary AI solutions architect and trusted advisor for the business function, supporting initiatives from ideation through to production.
• Ensure enterprise Data, ML, and AI architecture principles are applied pragmatically to deliver measurable business value.

• Partner with business stakeholders, product managers, and engineering teams to understand business use cases and constraints.
• Design and document end-to-end AI systems architectures, aligned with enterprise standards for:
  • Domain‑aligned AI capabilities and reusable AI services
  • AI lifecycle management frameworks (MLOps, LLMOps, Agent Ops)
  • AI‑aligned data patterns (feature stores, RAG pipelines, inference architectures)
• Review and guide solution designs to ensure they are secure, scalable, resilient, and cost-effective.

• Work closely with domain leadership to help shape domain data and AI strategy and roadmaps.
• Act as the voice of the business domain within the central Enterprise Architecture and AI communities.
• Provide structured feedback to central teams to evolve enterprise blueprints, platforms, and governance models based on practical experience.

• Represent the business function in Central Design Authority and architectural review forums.
• Ensure solutions meet enterprise security, AI governance, and AI risk standards while remaining delivery‑oriented and scalable.
• Champion architectural best practices, data literacy, and AI‑responsible design within the business function.
• Balance governance with enablement, ensuring standards accelerate rather than hinder delivery.

• Proactively identify opportunities where data, ML, and AI initiatives can deliver significant business value.
• Advise on MLOps, LLMOps, Agent Ops principles prioritisation and sequencing of initiatives based on feasibility, impact, and architectural readiness.
• Support the maturation of the domain’s data product and AI operating model.

• Deep knowledge of modern AI architectures on AWS, including Generative AI, RAG (Retrieval‑Augmented Generation), and large‑scale asynchronous inference workloads.
• Ability to translate enterprise business problems into AI‑driven Products, promoting decentralized model ownership while maintaining central standards for safety, evaluation, and reliability.
• Expert‑level experience designing and operating AWS/Data Bricks with…