Senior Applied AI Engineer – Prompting & Evaluation

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. Klipboard has offices in the UK, Ireland, The Netherlands, South Africa, Kenya and North America.

Klipboard is a global, growing business that embraces AI and emerging technologies to enhance customer outcomes, collaboration, and continuous improvement. We’re looking for people who are curious about or fluid with AI, open to change, and excited to learn how technology can improve the way we work and help our customers which is always supported by strong human insight and communication.

• 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.
• Design, build and refine prompts, context strategies and agentic workflows for AI features, ensuring that a confidently wrong answer does not get shipped.
• Build evaluation into everything – test prompts against real business cases at scale, measure quality honestly, and treat test results as the basis for improvement.
• Work across models and providers, choosing pragmatically on quality, cost and latency, and keep up as models, tools and providers change.
• Get deep into domain detail with product teams and subject matter experts to understand the business problem behind each feature.
• Coach engineers across teams to get dramatically more from AI coding tools and LLMs through pairing, reviews, workshops and patient one‑to‑one help.
• Build and maintain shared prompt patterns, reusable templates, evaluation harnesses and internal guides, so good practice spreads as assets.
• Run an internal community of practice where engineers share what is working, what failed and why, and make it a place people want to attend.
• Share measurable results with engineering leadership, highlighting where AI tooling is genuinely paying off and where it is not.
• Deliver AI features in products with proper evaluation and measurable quality standards.
• Embed prompt engineering and evaluation best practice across the R&D organisation.
• Maintain high standards for safety, accuracy and data handling in everything that ships.

• Large language model APIs across multiple providers (GPT, Claude, Llama and equivalents).
• AI coding tools such as Git Hub Copilot, Cursor or equivalents.
• Prompt engineering, context design and agentic workflow frameworks.
• Evaluation harnesses, evaluation datasets and automated test suites for AI outputs.
• Retrieval‑augmented generation, vector search, embeddings and retrieval pipelines (desired).
• LLM orchestration frameworks such as Lang Chain, Semantic Kernel or equivalents (desired).

• 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 in real work.
• Experience building evaluations or test harnesses for LLM outputs, and using them to improve quality measurably.
• Clear evidence of mentoring or coaching other engineers through workshops, training or community of practice.
• Daily fluency with AI coding tools such as Git Hub Copilot, Cursor or equivalents, with a…