Head of Artificial Intelligence

Head of Enterprise AI Platforms

Introduction to role

Are you ready to lead the charge in transforming healthcare through AI? This is an opportunity to drive the adoption of AI across every step of the biopharmaceutical value chain – from discovering new compounds to ensuring patient safety. As the Head of Enterprise AI Platforms, you will be at the forefront of this journey, shaping the development and deployment of pioneering AI solutions within a global, science-led organisation. Join us in revolutionising healthcare and making a meaningful impact on patients' lives worldwide.

Accountabilities

As the Head of Enterprise AI Platforms, you will be responsible for steering the organisation’s AWS AI ecosystem, ensuring seamless operation and integration into broader business platforms. You will lead a team of AI engineers and collaborate with a diverse set of partners to build a robust, secure, and cost-effective machine learning environment. Your strategic vision will guide the consolidation of existing AI platforms and influence AWS product roadmaps to align with a unified enterprise AI strategy. You will engage with senior AI leaders and data scientists to enable scalable machine learning models, leveraging your expertise to push technological boundaries and drive innovation.

Essential Skills / Experience

Developing technical strategies and aligning with partners across a sophisticated global organisation

Influencing and communicating strategy effectively

Budget and resource management (FTE, Outsourced Service Providers, Professional Services) for complex stakeholder groups

Strong software coding skills, with proficiency in Python (though exceptional ability in any language will be recognised)

Experience leading an enterprise platform and service, managing new customer demand and feature requests

Proven leadership of technical teams

Experience with SAFe agile principles and practices

Familiarity with internal security standards and frameworks

B.S. degree or equivalent experience in Computer Science or a related quantitative / analytical field

Significant experience with AWS cloud environments & services (e.g., SageMaker, Athena, S3, EC2, RDS, Glue, etc.)

Proven ability to build data science and machine learning environments to production standard

Modern DevOps mindset, using toolchains such as Docker and Git

Experience with infrastructure as code technologies (Ansible, Terraform, CloudFormation)

Ability to adapt standard machine learning methods to exploit modern parallel environments (distributed clusters, multicore SMP, GPU)

Desirable Skills / Experience

Experience in implementing & maintaining GxP-compliant life science systems

Relevant professional certifications

Experience building large-scale data processing pipelines (Hadoop / Spark, SQL)

Multi-cloud experience (AWS / Azure / GCP)