Bachelor's degree or equivalent practical experience.
10 years of experience with cloud native architecture in a customer-facing or support role.
Experience in conducting technical workshops, proof-of-concepts, and customer evaluations with executive leaders and stakeholders in the life sciences or pharmaceutical industries.
Experience with Artificial Intelligence (AI) Infrastructure (e.g., GPUs/TPUs), architectures, and technologies.
Preferred qualifications:
Master's degree in Computer Science, Engineering, Mathematics, a technical field, or equivalent practical experience.
Experience with Graphics Processing Unit/Tensor Processing Unit (GPU/TPU) computing and its application in scientific field on cloud platforms.
Experience with cloud services related to AI, data analytics, and scientific computing.
Knowledge of scientific workflows and software used in drug discovery (e.g., molecular modeling, simulations, cheminformatics).
Knowledge of industry compliance and security requirements related to Life Sciences (e.g., HIPAA, GxP).