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AI Engineer

Job in Leeds, West Yorkshire, ME17, England, UK
Listing for: Waystone
Full Time position
Listed on 2026-02-28
Job specializations:
  • Software Development
    AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below

For over 20 years, Waystone has been at the cutting edge of specialist services for the asset management industry – partnering with institutional investors, investment funds and asset managers. We work with our clients to help build, support, and protect investment structures and strategies worldwide. Our success depends upon our ability to attract and retain the best, most diverse talent and provide our employees with a broad spectrum of professional development opportunities.

Our workplace environment is an inclusive one, where employees can be themselves, reach their full potential and drive business results.

Summary:

Reporting to the AI & Technology Oversight Manager, the AI Engineer is responsible for embedding artificial intelligence capabilities into Waystone’s engineering, automation, and assurance ecosystems. Acting as a bridge between cutting‑edge AI technologies and existing high‑code and low‑code platforms, the role focuses on AI enablement rather than foundational model building, ensuring intelligence is thoughtfully integrated into systems and workflows. The AI Engineer designs, develops, and assures AI‑enabled solutions, improves automation efficiency, elevates engineering quality, and mentors teams on responsible and effective AI adoption.

The mission is to drive innovation, productivity, and intelligent automation across Waystone while upholding compliance, security, and architectural integrity. The role requires strong hands‑on engineering skills, practical understanding of agentic AI patterns, and the ability to guide teams on effective and responsible AI usage.

Essential Duties And Responsibilities AI Enablement and Integration
  • Hands‑on contributor to the design and development of AI‑enabled solutions, capable of writing both production‑quality code and rapid experimental prototypes.
  • Develop and implement AI‑enabled microservices, APIs, applications, and internal tools.
  • Integrate AI capabilities following secure, scalable engineering best practices.
  • Design, build and validate AI‑driven solutions leveraging providers such as OpenAI and Anthropic.
  • Enhance low‑code/no‑code automation platforms (e.g., Power Automate, n8n, Workato) by embedding intelligent processing and applying agentic patterns where relevant.
  • Implement Model Context Protocol (MCP) servers for secure AI‑to‑system connectivity.
  • Lead AI‑based document parsing and intelligent data extraction initiatives.
  • Contribute to educating and enabling Enterprise Capabilities areas, including Integration and Automation, by providing guidance, training, and best practices, e.g., on effective use of n8n agents.
  • Engage with business stakeholders to understand requirements, constraints, and key drivers, identifying and implementing high‑value AI opportunities across Waystone.
AI Engineering
  • Prototype AI features and iterate towards production‑ready capabilities.
  • Build agentic workflows using frameworks such as Lang Chain or Microsoft Agent Framework, with a solid understanding of agent fundamentals (tools, memory, orchestration, context control).
  • Implement AI agents with tool integration, memory, context control, and guardrails.
  • Develop retrieval‑augmented workflows to enhance context, reliability, and performance.
  • Perform quality assurance on AI outputs by implementing robust AI observability practices, including monitoring model behaviour, detecting anomalies, and ensuring visibility into AI performance and reliability.
  • Contribute to ongoing research and development, staying current with emerging AI tools, frameworks, and techniques to identify opportunities for innovation and improvement.
  • Apply sound judgment to determine when not to use AI, ensuring traditional deterministic solutions are chosen when they are safer, simpler, or more cost effective.
  • Ensure AI‑enabled solutions consider full total cost of ownership, including token consumption, performance, observability, and ongoing maintenance, with awareness of cost‑efficiency and model‑selection trade‑offs.
Knowledge Sharing, Mentoring And Governance
  • Mentor and support both technical and non‑technical staff (e.g. citizen developers), fostering knowledge sharing and strengthening AI fluency…
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