Job Description

776
Nationwide
Permanent
Competitive salary and excellent company benefits

Why choose us?

Choosing to work for SMS means choosing to make a difference.

We are changing how businesses and consumers use energy for the better, helping achieve a greener, sustainable, and more affordable energy system for everyone. Through our range of innovative energy solutions, we are delivering the future of smart energy - working closely with private and public sector partners we are playing a critical role in transforming and decarbonising the UK economy by 2050.

What's in it for you?

25 personal holiday days per year (with additional 8 public holidays) increasing to 30 personal days after 5 years of service (includes options to buy and sell) Hybrid working options (for some positions). Enhanced Maternity leave. Paternity and Adoption leave. 24/7 free and confidential employee assistance service. Simply Health plan offers a wide variety of benefits from cashback on everyday healthcare treatments like optical, dental and physio treatments. Discounted gym memberships and free 24/7 online GP. Life Insurance (4 x annual salary) Pension matching scheme (up to 5% of salary)

What's the role?

Step into a role where strategy meets engineering excellence. As our Lead Enterprise AI Engineer, you'll be the driving force turning bold business opportunities into production?ready AI solutions. You'll shape intelligent agents, craft next?generation conversational experiences using Microsoft Copilot and Databricks Mosaic AI, and architect the Semantic Layer that ensures our models deliver accurate, trusted insights every time.


If you're ready to take ownership of an organisation's AI future--and build the systems that make it real--this is your stage.


You will report to the Data, Analytics and AI Director and work remotely on a full?time, 40?hour contract.

Please note: The closing date for applications is Wednesday 21st January 2026.

Key responsibilities:

AI Solution Development & Agent Building

Design, build, and deploy low-code and pro-code AI agents using Microsoft Copilot tools to automate business workflows (e.g., HR queries, IT support, operational data retrieval). Develop custom RAG (Retrieval-Augmented Generation) solutions within Databricks to allow LLMs to reason over proprietary SMS documents and data. Integrate AI agents with enterprise systems (Dynamics 365, SharePoint, etc.) via APIs and Power Automate connectors.

Semantic Modelling & Databricks Genie Curation

Own the creation and maintenance of Databricks Genie Spaces. This involves translating complex database schemas into business-friendly semantic models. Define and govern standard metrics, dimensions, and synonyms within Unity Catalog to ensure the AI "speaks the language of the business." Continuously monitor Genie performance, reviewing "human feedback" on answers to refine the semantic model and improve accuracy over time.

Business Engagement & Prototyping

Partner with business stakeholders (Finance, Operations, Commercial) to decompose high-level use cases into technical requirements. Rapidly prototype AI solutions to demonstrate value and gain quick traction within business units. Act as a technical evangelist, demonstrating to non-technical teams how to interact with Genie spaces and Copilots effectively.

AI Operations (LLMOps) & Governance

Implement monitoring frameworks to track the cost, latency, and quality of AI model outputs. Ensure all AI solutions adhere to the organisation's data governance and security standards (e.g., preventing data leakage via LLMs). Manage the lifecycle of AI models and agents from development through to production and retirement.

To be considered for this role, we would love you to have:

Degree in Computer Science, Data Engineering, Artificial Intelligence, or related field, or equivalent industry experience. Deep hands-on experience with Azure/Microsoft Fabric ecosystem (specifically Copilot Studio & Power Platform) and Databricks (SQL, Unity Catalog, Mosaic AI). Strong ability to design data models for analytics. Experience with defining metrics layers (e.g., DBX semantic layer or Databricks Genie) is essential. Practical experience with Large Language Models (LLMs), Prompt Engineering, and RAG architectures. Proficient in Python (for data manipulation and API interaction) and SQL (for data modelling). Experience working with REST APIs and connecting disparate business systems. Ability to explain technical AI concepts to non-technical business users and translate their feedback into code.

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