Customer Facing AI Data Scientist - Systems Integrator

Keen to join a company that champions growth and development?Join a leading UK Managed Service Provider expanding into applied AI and LLM-based solutions for enterprise clients. The organisation is building a new AI capability that combines deep technical expertise with practical, commercially focused solutions for existing and prospective managed services customers.This company is looking for a Customer-Facing AI Data Scientist to work directly with client engineering leads and technical stakeholders, architecting LLM solutions, supporting design decisions, and translating advanced model knowledge into commercially viable outcomes. The role offers genuine ownership across LLM fine-tuning, evaluation, and deployment, with the opportunity to help shape a new AI practice within an established MSP.Responsibilities:Act as the primary technical point of contact for enterprise clients on LLM-based engagements, from scoping through to deployment.Design and architect LLM training, fine-tuning

and evaluation pipelines tailored to specific client use cases and data environments.Translate ambiguous client requirements into concrete technical architectures and delivery plans.Lead deep technical discovery sessions and whiteboard sessions with client engineering and data science teams.Own model performance, evaluation methodology, and responsible deployment recommendations for client-facing solutions.Partner with sales, account management, and delivery teams to ensure architectural decisions are technically sound and commercially deliverable within a managed services model.Skills/Must Have:Experience: 5+ years in applied data science or ML engineering, with direct exposure to LLM training or fine-tuning at a technical (not just API-consumption) level.Core Tech/Domain: Hands-on experience with transformer architectures, LLM pre-training or fine-tuning workflows, and modern ML frameworks (PyTorch, Hugging Face, or equivalent).Methodology/Protocols: Strong grounding in evaluation methodology, RAG and fine-tuning trade-offs, and production ML deployment patterns.Soft Skills: Confident and credible in front of senior technical stakeholders, comfortable with pushback in live technical discussions, able to hold a boardroom and a terminal equally well.Desirable Skills:Experience with distributed training infrastructure (multi-GPU, multi-node).Prior pre-sales, solutions architecture, or consulting background.Familiarity with model safety, alignment, or responsible AI evaluation frameworks.Salary:£120,000 #J-18808-Ljbffr