Software Engineer – AI Applications

Purpose of the role

Own the company's AI applications end-to-end.

You will build the products this transformation programme is ultimately about: retrieval engines across years of company documents, document processing pipelines that turn files into structured data, and AI applications used across the business every day.

Working within the Data & AI platform and architecture, you will own what users touch, what they adopt and the value they get from it.

Responsibilities

• Own AI applications from concept to production, ensuring adoption, quality and business impact.
• Sit with your users weekly: watch how they actually work, ship improvements and measure whether they are used.
• Engineer prompts, retrieval and agent workflows with evaluation as a habit, not an afterthought.
• Build backend services in Python and a clean internal front end (React or similar), without a designer.
• Consume the Gold layer and the document store the Data Engineer maintains, and feed requirements back.
• Run everything on approved EU-hosted model endpoints configured for zero data retention: commercially sensitive data never leaves the perimeter.
• Keep token and compute costs proportionate to the value shipped.
• Work daily with the Data Engineer on retrieval-ready data, the Cloud Platform Engineer on deployment and security, and the Product Manager on what users actually need. Document as you go.

Qualifications & Experience

• 5 to 7 years of software engineering experience, including designing, building and operating production services in Python.
• Experience delivering at least one LLM-powered product or feature to real users, with hands-on knowledge of RAG, embeddings, retrieval, prompt engineering and evaluation.
• Full-stack capability, with experience building internal applications and user-facing interfaces using React or similar frameworks.
• Strong understanding of LLM evaluation, including quality measurement, test set creation and failure analysis.
• Product mindset and experience working directly with business users, turning real problems into adopted solutions.
• Ability to balance speed, quality and pragmatism when developing AI products.
• An AI-first way of working, or strong enthusiasm to build one, using modern AI development and agent tools responsibly and effectively.

Nice to have

• Experience with agentic AI systems, including tool use, function calling, MCP, agent frameworks and evaluation frameworks.
• Experience with document processing, OCR and extracting structured information from complex documents.
• Experience with Azure OpenAI, Azure AI Foundry, Databricks Model Serving or similar AI platforms.
• Exposure to construction, engineering or other document-intensive industries.
• Working knowledge of data engineering concepts, including SQL and dbt.