Overview
Klipboard provides specialized software and services to deliver fully integrated trading and business management solutions to companies in the distributive trade worldwide. With a flexible hybrid work policy, employees spend three days in the office and two days working from home.
Role
As a hands‑on AI engineer you will take AI features from idea to shipped software, working quickly within established C# .NET codebases. Your work focuses on prompt design, model integration, evaluation, and ensuring production‑grade quality.
Key Responsibilities
- Build AI features quickly and properly – from prompts and context design through to full LLM integration in established C# .NET codebases.
- Make them production‑grade – error handling, fallbacks, latency management, logging, monitoring, and solid evaluation before any customer exposure.
- Stay sharp and share as you go – keeping up with a fast‑moving space and spreading knowledge through code, examples and conversation.
- Design and build prompts, context strategies and LLM integrations for product features where a confidently wrong price or stock answer is worse than no answer.
- Integrate AI capability into established codebases through clean service boundaries and respectful abstraction of existing patterns.
- Prototype in days, harden in weeks, and differentiate between corners that can be cut and those that cannot.
- Build evaluation alongside the feature, testing against real business cases and measuring quality honestly.
- Handle the unglamorous parts well: error handling, fallbacks for misbehaving models, latency, token cost, logging and monitoring.
- Work with the engineers who own each codebase, fitting in with their pipelines rather than parachuting in something unsustainable.
- Keep up as models, tools and providers change, choosing pragmatically on quality, cost and latency rather than habit.
- 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, ensuring the best prompt serves the real requirement.
Systems, Tools and Technology
- C# .NET (primary development language)
- Large language model APIs across multiple providers
- AI coding tools: GitHub Copilot, Cursor or equivalents
- Prompt engineering and context design patterns
- Retrieval‑augmented generation, vector search, embeddings (desirable)
- Evaluation frameworks and automated quality pipelines for AI outputs
Technical and Professional Expertise
- Solid production experience with C# .NET, including working in established codebases you did not write, and shipping changes safely.
- Hands‑on experience building with large language models: prompt design, context engineering and structured outputs in real work.
- A track record of shipping quickly, taking something from idea to working software within weeks rather than quarters.
- Experience testing or evaluating LLM outputs in a structured way, using the results to improve quality.
- Daily fluency with AI coding tools such as GitHub Copilot or Cursor.
Preferred Qualifications
- Retrieval‑augmented generation, agentic workflows, tool use, vector search or embeddings in production environments.
- Experience with LLM APIs across more than one provider, with a feel for their trade‑offs.
- Exposure to Klipboard’s sectors: distributive trades, rental, retail, automotive aftermarket parts or garage management.
- Experience modernising or extending long‑lived systems, in .NET or elsewhere.
- Familiarity with evaluation frameworks, test datasets or automated quality pipelines for AI outputs.
Success Indicators
- AI capability shipped into at least one established product with evaluation behind it within the first six months.
- Something built goes from idea to customers in weeks and holds up in production.
- Evaluation results have changed at least one decision, possibly ceasing a product that was not good enough to ship.
- Other engineers adopt techniques from your work, despite teaching not being your primary job.
- Clear explanation of the business problem behind each feature you built, not just the technical solution.
People, Collaboration & Culture
- Bias to action – build a small version today and learn from it rather than a large version after months.
- Honest about quality – measures results, shows working code, and does not ship something they would not stand behind.
- Respectful of existing code and the engineers who maintain it – established systems are prized and working within them is a valued skill.
- Curious about Klipboard’s customer trades where domain detail drives good prompts.
- Comfortable with change – the tools will evolve, and you will adapt comfortably.
Equal Opportunities
As a global company, we value and respect the diversity of our workforce, aiming to empower everyone to embrace each other's differences. We are committed to creating an inclusive workplace where diversity, equity, and inclusion are integral to our culture and business. If you require any help, adjustments or support during the interview and offer process, please advise our TA or HR team.
Company Information
Klipboard is a global, growing business that embraces AI and emerging technologies to enhance customer outcomes, collaboration and continuous improvement. We have offices in the UK, Ireland, the Netherlands, South Africa, Kenya and North America, serving clients from small traders to multinational enterprises.
