PHead of Enterprise AI Platforms /ppIntroduction to role /ppAre 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. /ppAccountabilities /ppAs 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. /ppEssential Skills/Experience /pulliDeveloping technical strategies and aligning with partners across a sophisticated global organisation /liliInfluencing and communicating strategy effectively /liliBudget and resource management (FTE, Outsourced Service Providers, Professional Services) for complex stakeholder groups /liliStrong software coding skills, with proficiency in Python (though exceptional ability in any language will be recognised) /liliExperience leading an enterprise platform and service, managing new customer demand and feature requests /liliProven leadership of technical teams /liliExperience with SAFe agile principles and practices /liliFamiliarity with internal security standards and frameworks /liliB.S. degree or equivalent experience in Computer Science or a related quantitative/analytical field /liliSignificant experience with AWS cloud environments services (e.g., SageMaker, Athena, S3, EC2, RDS, Glue, etc.) /liliProven ability to build data science and machine learning environments to production standard /liliModern DevOps mindset, using toolchains such as Docker and Git /liliExperience with infrastructure as code technologies (Ansible, Terraform, CloudFormation) /liliAbility to adapt standard machine learning methods to exploit modern parallel environments (distributed clusters, multicore SMP, GPU) /li /ulpDesirable Skills/Experience /pulliExperience in implementing maintaining GxP-compliant life science systems /liliRelevant professional certifications /liliExperience building large-scale data processing pipelines (Hadoop/Spark, SQL) /liliMulti-cloud experience (AWS/Azure/GCP) /li /ul