AI Engineer
Role details
Job location
Tech stack
Job description
If you decide that this AI Engineer position is the role for you, then you'll be joining the UK's largest group of property services, a business that is constantly looking to improve, and one that offers both exciting challenges and job satisfaction. What You'll Be Doing We are seeking a capable and solutionsâfocused AI Engineer to join our growing AI Team. This role blends Generative AI, Machine Learning (ML), Microsoft-centric software engineering, and integration, and is suited to someone who has delivered AI-powered solutions and is ready to deepen their expertise in an enterprise environment. You will work across Azure, M365, Copilot, Copilot Studio, Databricks, and modern engineering frameworks to deliver production-grade AI services under agreed architecture and security standards. The role includes hands-on experimentation and rapid proofâofâconcept (PoC) development, with guidance from senior engineers on governance, risk, and best practice. You will help scale AI safely and sustainably across our property and legal services domain. We can offer the successful candidate mentorship from Senior AI colleagues, support in architecture and governance, and opportunity to deepen Azure AI / Copilot / ML expertise., AI & GenAI Engineering
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Build and enhance GenAI solutions using Azure OpenAI, Azure AI Services, and Copilot extensibility, following agreed patterns.
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Implement RAG architectures (vector retrieval, embeddings, prompt strategies) with secure LLM integrations.
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Build conversational assistants and workflow automations using Copilot Studio and the Power Platform.
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Contribute to experimentation, prototyping, and PoC development to evaluate AI capabilities and feasibility.
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Support evaluation and integration of thirdâparty AI tools or APIs where required, working with the team to meet governance and security requirements.
Machine Leaning Engineering
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Develop and operationalise ML models with appropriate review and documentation.
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Translate prototypes into robust services, collaborating with engineering colleagues to meet non-functional requirements.
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Create ML pipelines and automate lifecycle workflows using team tooling and standards.
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Assist with monitoring, optimisation, escalating risks and issues where appropriate.
Microsoft Code-Based Development
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Build AI-enabled services and APIs using .NET/C#, Python, Azure Functions, and REST under guidance on patterns and quality.
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Use Visual Studio, VS Code, GitHub, and Azure DevOps for CI/CD.
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Contribute to deployments using infrastructure-as-code templates (e.g., Bicep or ARM), with support from senior engineers.
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Implement integrations with Logic Apps, Service Bus, and Event Grid using secure, approved patterns.
Data, Engineering & Integration
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Work with data and AI platforms such as Databricks and Azure data services.
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Build and maintain pipelines for ML and LLM workloads, partnering with data engineering where needed.
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Integrate internal and external systems using secure authentication and authorisation approaches.
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Follow responsible AI, privacy, and security standards, contributing to risk assessment and documentation.
Quality, Testing & Delivery
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Conduct evaluation, guardrail and regression testing.
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Document architectures, PoCs, and technical decisions.
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Collaborate with stakeholders to refine use cases and deliver solutions.
Our Hiring Process: You've checked out our job ad It's gathered your interest and you've applied using our easy application process If shortlisted you will attend a first stage interview via Microsoft Teams If all goes well, a final stage interview may follow If successful, we make the offer and get the ball rolling After joining us you can recommend friends to join us too, earning a referral bonus for each successful appointment!
Requirements
An AI Engineer, a strong Software Engineer transitioning into AI, or perhaps a Data/Automation Engineer with some GenAI delivery experience? Do you have working knowledge of Azure OpenAI? Proficient in either C#/.NET or Python? Based in the UK with valid right to work?, * Hands-on experience building solutions with Azure AI Services and integrating them into applications and/or data solutions.
- Working knowledge of Azure OpenAI and common GenAI patterns (prompting, evaluation, basic RAG).
- Some experience with ML delivery (training, packaging, deployment, monitoring) in a live environment.
- Proficiency in either C#/.NET or Python, plus SQL fundamentals.
- Understanding of vector search concepts (embeddings, chunking, retrieval) and secure API integration.
- Experience using Git-based workflows and CI/CD pipelines (e.g., GitHub or Azure DevOps).
- Strong communication and problem-solving skills, including clear technical documentation
Whilst not essential, we are especially keen to hear from candidates who can demonstrate knowledge and experience in one or more of the following areas: building RAG solutions end to end and improving answer quality; Copilot Studio connectors/actions and Power Platform ALM; Databricks, Fabric, or Azure ML in a delivery setting; working knowledge of infrastructure-as-code and cloud deployment practices; understanding of REST API design and microservices patterns; awarness of emerging agent patterns ie, MCP/structured agentic architectures; and/or relevant certifications such as Azure AI Engineer Associate, Azure Data Scientist Associate, Power Platform Developer or Solution Architect, Databricks ML or Generative AI certifications, or Emerging AI and AI Solution certifications.