Head of Machine Intelligence , AI

Compensation £100,000 – £120,000 basic + equity + performance‑related bonus + full benefits package Role: Head of AI (practice‑building & thought‑leadership) Location: UK‑based, fast‑growing data & AI consultancy for the energy sector Cloud: Strong AWS (multi‑cloud desirable, certs a plus) Line Management: Lead a small but growing practice (AI, MLOps, Data Science) We welcome part‑time, condensed hours, job‑shares and other arrangements – if you’re unsure, apply and let’s talk Diversity & Inclusion: We want a broad mix of people and perspectives Hypercube Consulting is a rapidly scaling data‑and‑AI specialist focused on the energy sector. We pair deep domain know‑how with modern technology to help utilities, renewables and low‑carbon innovators unlock value from data. As Head of AI you will own the AI discipline within Hypercube. That means setting best practice, evolving our technical guard‑rails, shaping packaged offerings and guiding learning pathways for every AI practitioner in the business. You’ll split your time roughly 40 % billable (hands‑on technical oversight) and 60 % leadership, R&D and commercial activity. Technical Vision – Define and continuously update AI/ML best practice, guard‑rails and reference architectures; Practice Building – Design the end‑to‑end learning journey for AI engineers, data scientists, and machine learning engineers; Delivery Oversight – Provide senior technical oversight on complex projects without being the day‑to‑day project lead, ensuring quality and de‑risking delivery RAG accelerators, model‑monitoring blueprints) into packaged offerings that shorten sales cycles and improve customer outcomes Commercial & Pre‑Sales – Partner with sales to scope opportunities, run demos, estimate effort and shape proposals; evangelise AI at conferences, meet‑ups and on our blog AI Stack: Python, SQL, mathematics and statistics essential Generative AI & LLMs: Designing and fine‑tuning foundation‑model solutions; MLOps / LLMOps: CI/CD for models, feature stores, experiment tracking (MLflow, SageMaker, Azure ML, Vertex, etc.) Building scalable AI pipelines on AWS or Azure; Python Excellence: performance optimisation; packaging & dependency management Data Engineering for AI: Streaming & batch pipelines (Spark/Databricks), vector databases, metadata & lineage Backend and cloud languages such as Spark, LangChain, Terraform Analytics and visualisation experience with tools like Power BI or Superset Event‑driven stacks (Kafka, Kinesis, Event Hubs) Formal certifications (AWS Professional / Azure Expert / TOGAF, etc.) Building or scaling a consulting practice Product‑management mindset – shaping features, pricing, go‑to‑market Strong commercial acumen – translating business value into technical roadmaps Shape AI strategy for leading energy players tackling net‑zero challenges Flexible Working: Remote/hybrid, part‑time or condensed options – we measure outcomes, not chair‑time Personal Brand: We sponsor conferences, blog posts and OSS work – your thought‑leadership is encouraged Performance-Related Bonus Enhanced Pension Private Health Insurance Health Cash Plan Cycle-to-Work Scheme Flexible Working (remote/hybrid options) Events & Community involvement Training & Events Budget Diversity & Inclusion Hypercube aims to mirror the diversity of wider society. If you need adjustments – flexible hours, interview tweaks, or anything else – just tell us. Apply via our careers page or reach out to the talent team on LinkedIn.