Principal AI Developer

For international candidates open to relocation, support is available

We are looking for a Principal AI/ML Engineer to provide technical leadership across the design, development, deployment and continuous improvement of enterprise‑grade AI and machine learning solutions.

The Principal AI/ML Engineer will work closely with data scientists, software engineers, cloud engineers, architects, product teams and senior stakeholders to translate complex business problems into scalable, secure and measurable AI/ML solutions. The role will also play a key part in mentoring engineers, improving delivery practices, and embedding responsible AI and robust engineering principles across projects.

• Lead the design, development and deployment of scalable AI/ML solutions, taking ownership of the full lifecycle from discovery and experimentation through to production delivery and continuous improvement.
• Define and govern AI/ML architecture, engineering standards and best practices, ensuring solutions are secure, maintainable, cost‑effective and aligned with wider business and technology strategies.
• Design, build and optimise machine learning, deep learning and generative AI solutions, selecting the most appropriate tools, frameworks and approaches to solve complex business challenges.
• Drive the adoption of MLOps practices, including CI/CD, model versioning, monitoring, observability, performance optimisation and lifecycle management.
• Collaborate closely with business stakeholders, product teams, architects, data engineers and software engineers to translate requirements into practical AI‑driven solutions that deliver measurable value.
• Provide technical leadership and mentorship to engineers, supporting capability development, design reviews, knowledge sharing and the adoption of engineering best practices.
• Lead technical discovery activities, proof‑of‑concepts and architecture assessments, helping shape AI strategy and identify opportunities where AI can improve business outcomes.
• Ensure robust documentation, governance and responsible AI principles are embedded throughout the delivery lifecycle, supporting transparency, compliance and operational excellence.
• Stay current with emerging AI technologies, frameworks and industry trends, evaluating their potential application and guiding the organisation's adoption of new capabilities

• Strong Python expertise and experience with frameworks such as PyTorch, Tensor Flow and Scikit‑learn.
• Deep understanding of machine learning, deep learning and Generative AI technologies.
• Experience with Azure, AWS or GCP.
• Strong knowledge of MLOps, CI/CD, testing and software engineering best practices.
• Proven experience leading technical teams and influencing architecture decisions.