Senior Applied AI Engineer – Prompting & Evaluation in London

At Klipboard we've introduced a flexible hybrid work policy, where employees spend three days in the office and two days working from home. This approach promotes a balanced work environment that combines office collaboration with the comfort and convenience of remote work.

Klipboard provides specialist software, services and support to deliver fully integrated trading and business management solutions to companies in the distributive trade – wherever they are in the world. With a unique depth of knowledge and experience in ERP/SaaS solutions, Klipboard has a wide range of clients including wholesalers, distributors, merchants and retailers from small traders to multinational enterprises. Our mission is simple: to design and deliver high performance, integrated ERP solutions that enable our distributive trade customers to source effectively, stock efficiently, sell profitably and service competitively.

This is a high-impact senior engineering role for someone who wants to shape how a large engineering organisation uses AI in real products and real development work. You will set patterns, create evaluation standards, coach engineers and help Klipboard turn AI from individual experimentation into repeatable, scalable engineering practice.

The role is two jobs in one: the craft of getting reliable, measurable results from large language models through prompt engineering, context design and evaluation; and making everyone around you better at it. Your success is measured less by what you personally produce and more by how quickly the engineers around you improve.

Key Responsibilities

• Practise the craft at a high level – designing, building and refining prompts, context strategies and agentic workflows for AI features in our products.
• Grow the engineers around you – coaching, pairing, workshops and building shared assets that spread good practice across hundreds of engineers.
• Set standards and keep the organisation honest – defining what good looks like for prompting, evaluation and context engineering, and maintaining those standards as tools change.

Key Activities and Contributions

• Design, build and refine prompts, context strategies and agentic workflows for AI features in Klipboard products.
• Build evaluation into everything – test prompts against real business cases at scale, measure quality honestly.
• Work across models and providers, choosing pragmatically on quality, cost and latency rather than loyalty.
• Coach engineers across teams to get dramatically more from AI coding tools and LLMs.
• Build and maintain shared prompt patterns, reusable templates, evaluation harnesses and internal guides.
• Run an internal community of practice where engineers share what is working, what failed and why.
• Help define what good looks like for prompting, context engineering and evaluation across R&D.
• Share measurable results with engineering leadership.

Technical and Professional Expertise

• Strong software engineering background with several years building and shipping production software.
• Substantial hands-on experience with large language models: prompt design, context engineering and structured outputs.
• Experience building evaluations or test harnesses for LLM outputs.
• Clear evidence of growing other engineers – through mentoring, teaching, internal training.
• Daily working fluency with AI coding tools such as GitHub Copilot, Cursor or equivalents.

Customer Experience

• Ensure AI features in Klipboard products give accurate, safe and trustworthy answers.
• Work with product teams and subject matter experts to understand the business problem behind each feature properly before building.
• Prevent confidently wrong answers from reaching customers.

Key Outcomes and Activities

• Engineers across several teams can point to specific things they now do better because of coaching and knowledge-sharing.
• At least one AI feature or workflow shipped per quarter with proper evaluation behind it.
• A living, used library of prompt patterns, templates and guides in place and growing.
• Community of practice running, well attended, and producing outputs teams actually reuse.
• Engineering leadership has a clearer, evidence-based picture of where AI is paying off.

Klipboard is embracing AI at pace across our products and ways of working. We’re looking for people who are curious about how AI can enhance productivity, decision-making and customer outcomes, and who are open to learning and adapting as this space evolves.