AI and Data Engineering Consultant

AI & Data Engineering Consultant (Energy & Utilities) Location: UK-based Experience: 8+ years Industry Focus: Energy, Utilities, Infrastructure, Asset-Intensive Organisations About the Role We are looking for an experienced AI and Data Engineering Consultant to help organisations unlock value from their data, knowledge, and operational processes through the application of modern AI technologies. You will work at the intersection of AI, data engineering, knowledge management, and business transformation, designing and delivering production-grade solutions that combine large language models (LLMs), agentic AI, semantic data architectures, and cloud-native data platforms. You will help clients transform fragmented information landscapes into trusted, AI-ready ecosystems that support decision-making, automation, and operational excellence. This role is particularly suited to candidates with experience in energy and utilities environments, where complex engineering, asset, operational, and regulatory data must be integrated and leveraged to drive business outcomes. What You'll Do

•  Design and deliver enterprise AI solutions using LLMs, Retrieval-Augmented Generation (RAG), and agentic AI architectures.
• Build and operationalise AI agents and multi-agent workflows that automate knowledge-intensive processes and support decision-making.
• Develop scalable data platforms and data engineering pipelines using modern cloud technologies.
• Create semantic data models, ontologies, knowledge graphs, and information architectures that support advanced analytics and AI applications.
• Translate complex business and operational requirements into robust technical solutions.
• Design data products and AI capabilities that integrate enterprise, engineering, asset, operational, and customer data.
• Support the end-to-end lifecycle of AI solutions, from strategy and architecture through implementation, testing, deployment, monitoring, and continuous improvement.
• Develop Power BI dashboards and data pipeline and data services for Analytical needs
• Work closely with business stakeholders, engineers, architects, and data teams to ensure successful adoption and measurable business value. What We're Looking For   Core Skills · AI Engineering and Generative AI
• Large Language Models (LLMs)
• Agentic AI and AI Agent Development
• Retrieval-Augmented Generation (RAG)
• Machine Learning and Predictive Analytics
• Data Engineering and Data Platform Delivery
• Analytics and Power BI
• Cloud Architecture, particularly Azure
• Python development
• ETL / ELT and data integration
• MLOps and production AI deployment Knowledge & Information Architecture · Semantic data modelling
• Ontology design and management
• Knowledge graph development
• Information architecture
• Metadata management
• Data governance and AI-ready data foundations   Industry Experience We are particularly interested in candidates with experience in one or more of the following: · Energy and utilities
• Electricity, gas, water, or renewable energy providers
• Asset-intensive industries
• Engineering and operational data environments
• Infrastructure management
• Maintenance and asset management
• Regulatory and compliance-driven organisations   Ideal Candidate Profile An AI and Data Engineering professional with experience delivering enterprise AI platforms, intelligent agents, semantic knowledge architectures, and cloud-based data solutions. Skilled in combining GenAI, data engineering, ontology modelling, and operational domain knowledge to create scalable AI solutions that solve complex business and operational challenges, particularly within the energy and utilities sector. You have successfully designed and delivered AI-enabled solutions that move beyond proof of concept into production. You understand how to connect business challenges with data, knowledge, and AI capabilities, and can balance strategic thinking with hands-on technical delivery. You are comfortable working across multiple disciplines, from data engineering and cloud architecture to ontology design and agent orchestration. Most importantly, you can apply these capabilities within operational environments, helping organisations in the energy and utilities sector improve efficiency, decision-making, workforce productivity, and knowledge management.