About the role
We are seeking a Lead, AI Enablement Technologies to run a cross-cutting strategic function within Engineering and Technology. This role makes AI a first-class, measured, and safely operated capability across R&D IT. You will own the engineering "how" of AI: infrastructure, technology choices, engineering practice, and the platform that business-facing AI products run on.
What you will do
Own the operational performance of the AI Enablement function across five key workloads: HPC and scientific compute, AI inference and serving infrastructure, agentic foundations, AI-assisted engineering, and AI upskilling for R&D.
Direct line management for area leads, guiding specialists in HPC, scientific AI inference, and engineering AI.
Drive the technology roadmap for AI infrastructure across R&D IT, including model serving stacks, inference optimisation patterns, guardrails frameworks, vector database choices, and evaluation harnesses.
Manage HPC investments, including GPU procurement and cluster lifecycle, grounded in utilisation data and scientific demand forecasts.
Partner with peer data, analytics, and bioinformatics IT functions to define API contracts, cost attribution models, and shared scientific-computing patterns.
Own the evaluation and safety framework for AI at scale, including red-teaming, prompt-injection testing, and model performance tracking.
Build consensus on cross-boundary technical patterns and author Architecture Decision Records (ADRs).
Establish and monitor key performance indicators (KPIs) for infrastructure utilisation, cost efficiency, and system reliability, ensuring accountability across the AI Enablement function.
Develop and deliver comprehensive capability-building programmes for R&D teams, including training on AI best practices, platform usage, and responsible AI principles.
Manage vendor relationships and technology partnerships to ensure optimal selection, integration, and support of AI infrastructure components and tools.
What you will bring
Expert-level technical depth in AI infrastructure and MLOps, including model serving at scale, inference optimization, vector databases, and LLM-adjacent tooling.
Strong scientific HPC literacy (e.g., Slurm, GPU scheduling, scientific-computing workflows) to credibly direct HPC specialists and engage with scientists.
Proven engineering leadership experience running specialist teams and hiring senior/staff engineers.
Strong strategic navigation skills to partner effectively across boundaries without being captured by vendors or peer functions.
Hands-on habits; you still read code, review architecture, and evaluate tools directly.
Exceptional communication skills, able to explain complex AI infrastructure to executives and engineers alike.
Demonstrated experience designing and implementing safety frameworks, including red-teaming methodologies, adversarial testing, and model performance evaluation at scale.
Proven track record in managing technology budgets, capital expenditure planning, and cost optimization across infrastructure investments.
Experience authoring and socializing technical architecture decisions and design documentation across cross-functional teams.
Strong vendor management and technology partnership experience, with ability to evaluate, negotiate, and integrate third-party solutions effectively.
Hands-on experience with popular ML frameworks, tools, and platforms (e.g., PyTorch, TensorFlow, Kubernetes, Ray, or equivalent) to maintain technical credibility and inform infrastructure decisions.
Demonstrated success leading large-scale technology initiatives or organizational transformations, with ability to drive adoption and change management across diverse stakeholder groups.
Strong metrics-driven mindset with proven ability to establish, track, and optimize key performance indicators for infrastructure utilization, cost efficiency, and system reliability.
Experience building and scaling high-performing engineering teams in fast-growing or matrix organizational environments.
Familiarity with responsible AI governance frameworks, compliance requirements, and industry best practices for AI safety and ethics.
Site Details
Jealott's Hill International Research Centre UK is situated in pleasant semi-rural surroundings between Bracknell and Maidenhead and is the place of work for approximately 800 Syngenta scientists and support staff. Jealott’s Hill is one of the main global research and development sites and key activities include research into discovery of new active ingredients, new formulation technologies, product safety and technical support of our product range.
What we offer
Extensive benefits package including a generous pension scheme, bonus scheme, private medical & life insurance.
Up to 31.5 days annual holiday.
Flexible working
We offer a position which contributes to valuable and impactful work in a stimulating and international environment.
The opportunity to develop and apply your science within the chemical industry.
The chance to work as part of a global team to address the current and future needs of the agricultural sector.
Learning culture and wide range of training options.
Syngenta has been ranked as a top 5 employer and number 1 in agriculture by Science Journal.
Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status. Learn more about our D&I initiatives here: https://www.syngenta.com/careers/working-syngenta/diversity-and-inclusion