AI Software Engineer

• Deliver AI features end-to-end, from requirement understanding through to shipped, evaluated product capability.
• Build AI features quickly and properly, from prompts and context design through to full LLM integration in established C# .NET codebases.
• Make solutions production-grade with error handling, fallbacks, latency management, logging, monitoring and solid evaluation before customer release.
• Design and build prompts, context strategies and LLM integrations for product features.
• Work primarily in C# .NET, integrating AI capability into established codebases through clean service boundaries and sensible abstractions.
• Prototype in days, harden in weeks, and know the difference between a corner that can be cut and one that cannot.
• Build evaluation alongside the feature, test against real business cases, and measure quality honestly.
• Handle the unglamorous parts well, including error handling, fallbacks when a model misbehaves, latency, token cost, logging and monitoring.
• Work with the engineers who own each codebase, fitting in with their patterns and pipelines so the work remains maintainable.
• Keep up as models, tools and providers change, and choose pragmatically on quality, cost and latency.
• Share what you learn with engineers around you through code, examples and conversation.
• Work with product managers, product owners and subject matter experts to understand the business problem properly.
• Leave documentation in better shape than you found it so the next engineer can pick up your work without friction.
• Contribute to shared knowledge and engineering standards as the teams AI practice matures.

Technologies:

• AI
• C#
• Copilot
• Cursor
• GitHub
• LLM
• ASP.NET
• ERP
• Support
• LESS
• RAG

• Solid production experience with C# .NET, including working in established codebases and shipping changes safely.
• Hands-on experience building with large language models, including prompt design, context engineering and structured outputs.
• A track record of shipping quickly, with examples of taking something from idea to working software in weeks rather than quarters.
• Experience testing or evaluating LLM outputs in a structured way and using the results to improve quality.
• Daily fluency with AI coding tools such as GitHub Copilot, Cursor or equivalents.
• Preferred: experience with retrieval-augmented generation, agentic workflows, tool use, vector search or embeddings in production.
• Preferred: experience with LLM APIs across more than one provider and an understanding of their trade-offs.
• Preferred: exposure to distributive trades, rental, retail, automotive aftermarket parts or garage management.
• Preferred: experience modernising or extending long-lived systems, in .NET or elsewhere.
• Preferred: familiarity with evaluation frameworks, test datasets or automated quality pipelines for AI outputs.

We are Klipboard, formerly Kerridge Commercial Systems (KCS), a global software business delivering fully integrated trading and business management solutions for the distributive trade and related sectors, including distribution, automotive, retail, rental, transport management, manufacturing and field service management. We operate across offices in the UK, Ireland, the Netherlands, South Africa, Kenya and North America, and we are growing as we enter our next chapter. We offer a flexible hybrid working policy with three days in the office and two days working from home, supporting collaboration and balance. We are embracing AI and emerging technologies to improve customer outcomes, collaboration and continuous improvement, and we value diversity, inclusion and the opportunity for people to learn and adapt with us.