AI ENGINEERING LEAD – design

AI ENGINEERING LEAD – design & build end-to-end AI SOLUTIONS for leading global Wellness & HealthTech Business – LONDON, £120K – £130KThis is an exceptional opportunity for an Artificial Intelligence Engineering Lead with advanced quantitative analytical skills to design, build, and run end-to-end AI solutions for a leading Wellness/HealthTech business based in London. The role offers a salary of £120K – £130K.THE COMPANY:This globally recognised brand is a HealthTech & Wellness company that blends smart technology and world-class facilities into transformative wellbeing experiences. They are a next‑generation HealthTech brand using intelligent tools, digital platforms, and science‑backed training environments to optimise how people move, recover, and live. Their digital innovation journey is in full swing, and AI innovation will enhance the experience for over 1 million consumers.THE ROLE:The company is scaling AI safely, responsibly, and at speed across multiple countries. They are building a world‑class team of AI engineers who can design, build, and run AI solutions that millions of consumers use daily. As Lead AI Engineer, you will own entire problem spaces, lead mission‑critical initiatives, and shape how AI is delivered across the organisation. You will intersect software engineering, data engineering, machine learning, and quantitative analytics, working from problem framing through to deployment, monitoring, and scaling worldwide.WHAT YOU’LL DO:Own and lead AI across an entire domain (e.g., CRM & personalisation, operations optimisation, digital coaching), defining roadmaps, making architectural decisions, and guiding teams through discovery, experimentation, and delivery.Build production‑grade AI systems: from prototypes to scaled deployments, designing and shipping solutions that power real‑world experiences such as personalised journeys, churn prediction, lead scoring, RAG‑based knowledge assistants, energy optimisation, operational AI tools, and more.Analyse and prepare data for AI use‑cases across consumer behaviour, CRM interactions, digital journeys, operations, marketing and sales, energy consumption. Build and evaluate models using techniques such as regression, tree‑based methods, uplift models, time‑series forecasting, LLMs, generative AI, prompt engineering, retrieval‑augmented generation, fine‑tuning. Design prediction models for churn, propensity, next best action, lead scoring, lifetime value. Set technical direction, support synthetic personas, segmentation, marketing mix models, and ensure evaluation consistency.Partner across the business: work with Marketing, Digital, Operations, Finance, and Legal to turn ambiguous problems into structured AI opportunities, define hypotheses and success metrics, run rapid A/B tests and pilots, align multiple teams, and communicate model limits, trade‑offs, risks, and value.Architect and build APIs, services, pipelines, integrations, guardrails, and monitoring frameworks to guarantee safety, reliability, scalability, cost‑efficiency, and compliance.Lead technical delivery across markets: mentor engineers and data scientists, review designs, coordinate external partners, and ensure production readiness before global scaling.Shape the AI engineering culture: contribute patterns, templates, starter kits, documentation, playbooks, demos, training sessions, and hiring to raise the bar for the team.REQUIRED SKILLS:8+ years of applied ML, data science, quantitative analytics, and software engineering with significant AI/ML responsibility.Track record of shipping production AI solutions end‑to‑end.Experience leading complex AI initiatives and engineering teams.Strong background in customer analytics, personalisation, operations optimisation, marketing optimisation, conversational AI, or related domains.Expertise in Python and SQL.Strong system design and engineering fundamentals.Hands‑on with ML frameworks: scikit‑learn, XGBoost, PyTorch, TensorFlow, LightGBM.Experience with LLMs, prompt design, RAG, evaluation frameworks.Familiarity with data engineering and modern MLOps (registries, pipelines, CI/CD, monitoring).Cloud fluency.Comfortable switching between discovery and delivery.Strong appreciation for privacy, governance, and responsible AI.Seniority levelMid‑Senior levelEmployment typeFull‑timeJob functionInformation Technology #J-18808-Ljbffr