R&D Analytics - AI Developer

Company Description About Syngenta At Syngenta Vegetable Seeds, we’re passionate about helping people in the vegetable industry succeed and putting growers at the heart of all that we do. Our energies are focused on creating solutions that help them get more out of their crops, now and in the future. A commitment in every seed. We do this by protecting seed, bulbs, or small plant quality from the start to enable growers to achieve the highest yield potentials in their operations;

continually investing in R&D to bring cutting-edge innovations to the market; and striving to make a real-world difference through more sustainable practices on farms, in shipping, and at the grocery store.

Job Description At Syngenta, our goal is to build the most collaborative and trustworthy team in agriculture, providing top-quality seeds and innovative crop protection solutions that improve farmers' success. To support this mission, Syngenta’s Analytics & Data Sciences Team is seeking an R&D Analytics - AI Developer in Durham, NC.This role will build software solutions that enable R&D teams to analyze experimental, phenotypic, genotypic, environmental, operational, and pipeline data  successful candidate will combine strong software engineering, applied AI, and scientific data understanding to deliver tools that improve decision-making across Vegetable R&D.The

role requires fluency in modern AI-assisted development tools, including internal AI platforms, while also being able to design solutions that go beyond generic AI by embedding R&D-specific models, datasets, workflows, and domain logic.

We are looking for someone who does not simply use AI tools, but knows how to build beyond them. The ideal candidate will use AI platforms and modern AI development assistants to accelerate delivery, while also creating differentiated R&D solutions that depend on Syngenta’s scientific data, models, experimental context, and domain expertise.

Accountabilities:

Design and build data pipelines to support the development and deployment of machine learning models and advanced analytics.

Build analytical software and AI solutions that integrate R&D-specific data, models, and decision frameworks into intuitive user workflows.

Build application containerization and orchestration within a cloud environment.

Managing software deployment and configuration in non-production and production environments.

Partner with R&D scientists, data scientists, and analytics teams to translate scientific and operational needs into scalable software solutions.

Use AI-assisted software development tools to improve productivity, code quality, documentation, testing, while maintaining strong engineering judgment and accountability for final outputs.

Evaluate emerging AI, agentic AI, and automation capabilities and identify where they can responsibly improve R&D analytics, experimentation, and decision support.

Ensure solutions are scientifically valid, explainable where needed, reliable in production, and aligned with data governance, model governance, security, and compliance expectations.

Qualifications

PLEASE NOTE:

Candidates must reside in and be permanently authorized to work in the United States without current or future employer sponsorship. This comprises, but is not limited to, OPT, CPT, and H-1B visa holders.

Master or PhD in Data Science, Artificial Intelligence, Computer Science, Quantitative Genetics, or a related fieldA minimum of 5 years of professional software engineering experience, with at least 3 years building and maintaining production systems in Python.

Familiarity with AI and machine learning frameworks.

Strong knowledge and experience of Agentic AI and large language models.

Proven experience designing, building, and maintaining…