AI Solutions Developer & Data Steward

Join Vylor—Powering the Future of Agriculture At Vylor, we’re advancing agriculture through breakthrough science—combining elite germplasm, cutting-edge biotech, and next-generation expertise in gene editing and molecular breeding. Our portfolio includes trusted industry brands like Pioneer, Brevant, and Hoegemeyer, delivering performance farmers rely on.

Join us to help scale innovation globally and shape what’s next in crop science.

We are seeking a highly motivated and versatile AI Solutions Developer & Data Steward to join the Trait Analytics and Computational Discovery team edded directly Biotechnology, you will bring together two complementary strengths: ensuring the research data we rely on is trustworthy, well-organized, and ready for analysis, and rapidly building intelligent, LLM- and agent-powered solutions that accelerate scientific discovery.

Rather than shipping formal production software, you will thrive on delivering nimble point solutions, proofs of concept, and prototypes that put modern AI directly into the hands of researchers. You will work shoulder-to-shoulder with scientists to understand their day-to-day challenges, identify where AI agents and better data practices can unlock value, and turn those insights into working tools, often in days rather than months.

This is an exciting opportunity to operate at the frontier of generative and agentic AI while making a tangible impact on agricultural research and innovation.

Key Responsibilities Design and build AI agents, LLM-powered workflows, and retrieval-augmented (RAG) solutions that address specific research needs.

Partner with Vylor’s Enterprise Digital group to ensure AI solutions and workflows align with company security, privacy, and compliance standards.

Engage with Vylor’s Enterprise Digital group to stay current on emerging technologies, AI capabilities, and best practices, ensuring research solutions align with strategic technology direction.

Rapidly prototype point solutions and proofs of concept, iterating closely with scientists to refine and validate them.

Integrate large language models, APIs, and modern AI tooling into practical, research-facing applications.

Curate, organize, and maintain research datasets to ensure they are accurate, well-documented, and analysis-ready.

Champion FAIR data principles (Findable, Accessible, Interoperable, Reusable) and sound data governance across the research groups.

Build and maintain data pipelines, documentation, and metadata that make datasets discoverable and reusable—including as high-quality inputs for AI agents and models.

Partner with researchers to improve data quality, consistency, and provenance at the source.

Stay current with the fast-moving landscape of generative AI, agent frameworks, and machine learning, and bring emerging techniques into the team's toolkit.

Qualifications Bachelor's degree in Computer Science, Data Science, Mathematics, a Biological Science, or a related field. Postgraduate degree preferred.

Hands-on experience with modern AI/ML, including large language models and, ideally, agent frameworks or LLM orchestration tools (e.g., Lang Chain, Llama Index, or similar).Strong programming skills, particularly in Python (R or other languages a plus).Familiarity with data management best practices—data curation, pipelines, metadata, and governance.

A prototyping mindset: comfortable working with ambiguity, iterating quickly, and delivering usable solutions in a research setting.

Excellent problem-solving, analytical, communication, and collaboration skills, with the ability to translate scientific needs into technical solutions.

Curiosity about agriculture and the life sciences, and enthusiasm for applying cutting-edge AI to real-world scientific…