We are currently seeking a Lead AI Engineer to work with our public sector client 6 months contract £(Apply online only) inside IR35 Location: London Bristol or Manchester / Hybrid / Flexible on remote working The ideal candidates will have a proven Artificial intelligence engineering background within public sector ideally holding active SC clearance or have government project experience Skills & responsibilities: Ideating and developing one or more AI projects. These could be fully-fledged internal applications the incubator is building. Alternatively, they might be services we're building for the government's biggest missions in collaboration with other departments, where we work closely with technical counterparts. Writing and reviewing code daily. Collaborating with cross-functional teams and senior stakeholders to quickly understand customer needs and translate them into pragmatic technical solutions leveraging AI. Leading the design and establishment of frameworks, tools and processes to responsibly develop, deploy and monitor AI products. Evangelising best practices in applied AI across government. Staying on top of the latest developments in AI, including new models and paradigms. Proficiency in Python. An understanding of deploying and monitoring such systems in a cloud environment. Familiarity with tools for working with Large Language Models via API or in a local context (e.g. HuggingFace transformers). Experience with natural language processing, deep learning and generative AI.Nive to have: Building AI agents, or products that rely on AI agents Developing and working with tools and interfaces for AI applications (e.g. Anthropic's Model Context Protocol) Training traditional Machine Learning and Deep Learning models Hands-on experience with containerisation technologies such as Docker. Experience designing software services with respect to infrastructure, considering dependencies like databases and message queues, cloud environments, and pre-existing services with which yours must collaborate. Proven ability to collaborate with "non-engineering" disciplines, such as design and user research, to plan and deliver work of provable value as part of a product team, including prioritising, breaking down and sequencing technical work to achieve the best possible outcomes