UK based Remote First – Occasional Travel to London
Up to £130,000
You will be responsible for delivering production-grade AI solutions for enterprise clients, while also helping define engineering standards, mentoring AI engineers, and influencing how AI capability is built, scaled, and delivered across multiple engagements. This is a role for someone who enjoys operating at the intersection of technical delivery, architecture, and stakeholder engagement, with a strong focus on turning AI concepts into real-world business value.
You will lead the design, build, and deployment of AI and machine learning solutions across enterprise client environments. This includes developing production-ready AI systems, including LLM and agentic solutions, and ensuring they are robust, scalable, and responsibly designed.
You will work closely with clients to understand business challenges, lead technical workshops, and translate complex AI concepts into clear, practical solution options. You will also guide delivery teams through implementation, ensuring engineering quality across areas such as CI/CD, testing, model monitoring, observability, and performance optimisation.
In addition, you will play a key role in shaping solution architecture, evaluating AI tools and frameworks, and introducing best practices across MLOps, model lifecycle management, and responsible AI. You will also support pre-sales activities and contribute to shaping AI roadmaps and client propositions.
You will provide technical leadership across multiple AI delivery teams, ensuring solutions are delivered to a high standard and aligned with client objectives. You will design and implement end-to-end AI systems using modern cloud and data platforms such as Azure AI Foundry, Azure Machine Learning, Databricks, AWS SageMaker, or Bedrock.
You will build and deploy production-grade ML and AI solutions, including model evaluation, monitoring, drift detection, and operational observability. You will also implement and oversee MLOps practices such as CI/CD pipelines, model registries, and Infrastructure as Code.
Alongside delivery, you will coach and mentor engineers, contribute to internal capability development, and help define reusable engineering patterns and accelerators across the AI practice.
We are looking for experienced AI Engineers or AI Engineering Leads with a strong background in delivering production-grade AI solutions in enterprise environments. You should have strong Python engineering skills and experience building and deploying ML or AI systems into production.
You will have hands-on experience with modern cloud AI platforms such as Azure AI services, Azure Machine Learning, Databricks, AWS SageMaker, or Bedrock. You should also have a strong understanding of MLOps practices, including CI/CD, model monitoring, observability, and infrastructure automation.
Experience leading technical teams, guiding engineers, and delivering client-facing AI solutions is essential, along with the ability to translate complex AI concepts into clear, actionable guidance for both technical and non-technical stakeholders.
Experience with LLM-based systems, agent frameworks, prompt engineering, vector databases, and orchestration tools would be highly beneficial. Exposure to responsible AI practices, human-in-the-loop (HITL) design, and enterprise AI governance frameworks would also be advantageous.
Experience in consulting environments, pre-sales support, or shaping AI strategy and roadmaps would be a strong plus, along with familiarity across multiple cloud ecosystems.
This role offers the opportunity to shape and deliver cutting-edge AI solutions across enterprise organisations, where your work will directly influence how clients adopt and operationalise AI. You will bridge the gap between strategy and delivery, helping clients move from early AI exploration into production-grade systems that deliver measurable business value.
If you are an experienced AI Engineering Lead who enjoys combining hands-on technical delivery with client-facing consulting and leadership, we would like to hear from you.