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For Companies At a Glance
- Tasks: Lead AI projects, build intelligent agents, and bridge business needs with tech solutions.
- Company: Join a forward-thinking company focused on AI innovation and collaboration.
- Benefits: Enjoy remote work, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact by operationalising AI strategies and transforming business processes.
- Qualifications: Experience in AI engineering, coding skills in Python and SQL, and strong communication abilities.
- Other info: Dynamic role with excellent career advancement potential in a cutting-edge tech environment.
The predicted salary is between 48000 - 84000 £ per year.
The Lead Enterprise AI Engineer is a hands-on technical role responsible for operationalising the organisation’s AI strategy. This individual will bridge the gap between business opportunities and technical implementation, taking use cases from concept to production. The primary focus is to build and deploy intelligent agents and conversational interfaces using Microsoft Copilot tools and Databricks Mosaic AI. A critical component of this role is the curation of the "Semantic Layer"—to ensure AI models provide accurate, trusted answers to business questions.
- 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.
Skills and Knowledge:
- Core Tech Stack: Deep hands-on experience with Azure/Microsoft Fabric ecosystem (specifically Copilot Studio & Power Platform) and Databricks (SQL, Unity Catalog, Mosaic AI).
- Semantic Modelling: Strong ability to design data models for analytics. Experience with defining metrics layers (e.g., DBX semantic layer or Databricks Genie) is essential.
- LLM & AI Engineering: Practical experience with Large Language Models (LLMs), Prompt Engineering, and RAG architectures.
- Coding: Proficient in Python (for data manipulation and API interaction) and SQL (for data modelling).
- Integration: Experience working with REST APIs and connecting disparate business systems.
- Communication: Ability to explain technical AI concepts to non-technical business users and translate their feedback into code.
Lead Enterprise AI Engineer in Doncaster employer: Multitask Personnel
Contact Detail:
Multitask Personnel Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Enterprise AI Engineer in Doncaster
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Lead Enterprise AI Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those using Microsoft Copilot and Databricks. We want to see how you’ve turned concepts into real-world applications—this is your chance to shine!
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and soft skills. We recommend practising common interview questions related to AI engineering and thinking about how you’d explain complex concepts to non-techies.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Lead Enterprise AI Engineer in Doncaster
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Lead Enterprise AI Engineer role. Highlight your hands-on experience with Microsoft Copilot tools and Databricks, as well as any relevant projects you've worked on.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've operationalised AI strategies in the past and how you can bridge the gap between business needs and technical solutions.
Showcase Your Technical Skills: Don’t shy away from showcasing your technical prowess! Mention your experience with Python, SQL, and LLMs, and how you've used these skills to develop AI solutions. We want to see your coding chops!
Apply Through Our Website: For the best chance of success, make sure to apply through our website. This way, we can easily track your application and get back to you quicker. Plus, it shows you're keen on joining the StudySmarter team!
How to prepare for a job interview at Multitask Personnel
✨Know Your Tech Stack
Make sure you’re well-versed in the Azure/Microsoft Fabric ecosystem, especially Copilot Studio and Databricks. Brush up on your Python and SQL skills, as you'll likely be asked to demonstrate your coding abilities or discuss how you've used these technologies in past projects.
✨Understand Semantic Modelling
Familiarise yourself with semantic modelling concepts and be ready to discuss how you've designed data models for analytics. Be prepared to explain how you would create and maintain Databricks Genie Spaces and ensure that AI solutions speak the language of the business.
✨Engage with Business Stakeholders
Think about examples where you've partnered with business teams to translate high-level use cases into technical requirements. Show that you can bridge the gap between technical and non-technical teams, and be ready to share how you’ve demonstrated AI solutions to non-technical users.
✨Showcase Your AI Operations Knowledge
Be prepared to discuss how you would implement monitoring frameworks for AI model outputs. Highlight your understanding of data governance and security standards, and share any experiences you have managing the lifecycle of AI models from development to retirement.
