We are working with a client who is a global leader in consulting, technology services, and digital transformation,mitted to delivering positive change through technology and human collaboration. They are supporting a major critical national infrastructure transformation programme which is establishing a new dedicated AI team. The programme aims to accelerate the adoption of advanced AI capabilities, including: Agentic AI frameworks, Large Language Models (LLMs), and AI-driven enhancements to existing enterprise systems. These three new contracts will play a key part in integrating AI into production environments, ensuring safe, scalable, anderned deployment across the Software Delivery Life Cycle.
The successful candidate will support the integration of AI/ML models into enterprise systems, working closely with architects, engineers, and data teams. This programme is focused on: Scaling AI capability across aplex enterprise landscape. Transitioning from proof-of-concept to production AI systems. Embedding AI into existing SDLC and operational workflows. Establishingernance for safe and controlled AI adoption. You will support architects and lead engineers in integrating AI/ML models (including LLMs and agenticponents) into enterprise systems. Prepare and manage model inputs/outputs, validation processes, and interaction patterns. Collaborate with data engineers to ensure data pipelines meet model requirements (quality, lineage, reliability). Execute structured model testing, performance evaluation, and safety/bias checks. Support prompternance, including documentation of Prompt structures, Versioning, Constraints and evaluation criteria. Assist in managing AI-related risks, including Hallucination handling, Error recovery, High-risk decision boundaries.
To be considered for these contracts you must be able to demonstrate strong experience in AWS cloud environments with a background in application development within cloud migration programmes. You should have exposure to AI/ML integration within enterprise systems. Experience implementing ML monitoring frameworks (drift detection, model health, quality metrics). Exposure to DevOps integration of model artefacts into deployment pipelines. Ability to document model lifecycle, dependencies, and SDLC traceability. Understanding of AIernance and operational controls. Ability to translate AI outputs and constraints clearly to business stakeholders.
Please be clear that only candidates that meet the above criteria with the right to work, and that have been resident in the UK for the last 5 years or longer will be considered. No sponsorship is available. This role will allow for remote working here in the UK, but you must be able to attend key client sites in London and the Hampshire area when needed. #4798395 - Matthew O Dwyer