Delivery Manager, AI

Your objectives

• Lead the architecture and delivery of enterprise AI platforms and solutions, ensuring alignment with client business objectives, technology standards, and governance requirements.
• Solve the hardest problems with AI to deliver social and economic value.
• Build and lead a world-class AI team.
• Develop and maintain relationships with a broad range of clients, colleagues, and partners across a variety of contexts and formats.
• Inspire, mentor, and develop junior team members.
• Maintain a culture of excellence and lead with confidence, charisma, context, and humility working effectively at all levels.
• Create and deliver technical blogs & thought leadership on AI.
• Invest continuously in building and extending your knowledge and skills.

Your background

• Exceptional expertise in delivering AI engineering, machine learning and data science projects.
• Experience architecting and delivering cloud-native AI and data platforms on AWS, Azure, or GCP, including infrastructure, platform, and application layers.
• Experience leading cross-functional engineering teams comprising AI Engineers, Software Engineers, Data Engineers, DevOps Engineers, and Solution Architects.
• Strong understanding of modern software architecture, cloud-native development, microservices, containerisation, Kubernetes, and CI/CD practices.
• Experience delivering complex public sector or enterprise projects as a Technical Lead or Solution Architect will be a plus
• Practical hands-on experience to assist in the AI development lifecycle.
• 5+ years of experience delivering and managing AI solutions through incubation, proofs-of-concept, to deployment and commercialization.
• Strong ability to develop and maintain relationships amongst clients, colleagues, and partners.
• Ability to develop and deliver client proposals, and build consensus supported by detailed analysis, deep expertise and effective communication.
• Broad experience of NLP, computer vision, classification & recommendation systems, reinforcement learning and time series.
• Broad experience of model deployment, canary releases and implementation on cloud.
• Demonstrated ability to guide, develop and mentor AI and data engineers.
• Demonstrated ability to create technical blogs & thought leadership on AI.
• Active engagement in the AI community taking and giving courses, following podcasts, reading books, attending meetups, and developing projects.