R&D Analytics AI Developer

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 Syngentas Analytics & Data Sciences Team is seeking an R&D Analytics - AI Developer. 

This role will build software solutions that enable R&D teams to analyze experimental phenotypic genotypic environmental operational and pipeline data at scale. The 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 Syngentas 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.

WL4A

Qualifications :

• Master or PhD in Data Science Artificial Intelligence Computer Science Quantitative Genetics or a related field
• A 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 end-to-end software solutions.
• Strong Python programming and software engineering skills.
• Experience with big data platforms and technologies (e.g. Snowflake Databricks).
• Experience packaging deploying and monitoring ML models in production.
• Proficiency in developing cloud-native applications and deploying to cloud environments especially AWS.
• Experience with API technologies (e.g. RESTful APIs or GraphQL)
• Experience developing software products or analytical applications for scientific R&D agricultural biological or similarly complex data domains.
• Demonstrated ability to use AI coding assistants enterprise AI platforms or agentic AI tools to accelerate software delivery while applying independent technical review testing and validation.
• Familiarity with responsible AI practices including model evaluation bias/error assessment traceability prompt/version management and human-in-the-loop workflows.

Additional Information :

Location: 

You may work from any site in Poland following the local guidances of the hybrid model. 

#LI-DNI

Remote Work :

No

Employment Type :

Full-time