AI Forward Engineer

Location: Buckinghamshire, UK - Hybrid - 2 days p/w

Day Rate: £600 p/d - OutsideIR35

Type: Contract

Length: 6 Months

Start Date: ASAP

Purpose

The role will embed directly into the organisation's operational teams and solve important business problems using an AI and operational data platform. You will combine the curiosity of a strategist, the discipline of an engineer and the pragmatism of an operator. Working alongside the people doing the work, you will understand how the business operates, identify where data, systems and processes get in the way, and design and build better ways of working.

Key Responsibilities:

Understand How the Business Really Works

• Embed with functions including Finance, People, Revenue, Customer, Operations and M&A integration.
• Spend time with the people doing the work, beyond reviewing process documentation.
• Understand workflows, decisions, bottlenecks, workarounds and sources of friction.
• Map the systems and data supporting those processes.
• Identify where information gets duplicated, delayed, lost or mistrusted.
• Understand which decisions matter and what information people need to make them.
• Challenge processes that exist because "that's how we've always done it".

Own the Journey from Prototype to Production:

• Take solutions through the full journey: Problem → Prototype → MVP → Production → Adoption → Measured Impact.
• Take responsibility for architecture, data quality, security, permissions, reliability, testing and evaluation, controls and auditability, user experience, adoption, documentation and ongoing ownership

Build an AI-First Operating Company:

• Help determine what should be automated, what should be augmented and where human judgement remains essential.
• Establish where agents can act independently, what controls and approvals are required, and how AI performance should be evaluated
• Identify how processes should change as capability improves.
• Focus on better decisions, faster execution and less operational friction.

Key Skills, Experience and Qualifications:

Engineering and Platform Fluency

• Experience designing or building production systems.
• Strong understanding of data modelling, APIs and integrations.
• Experience working across modern SaaS and enterprise platforms.
• Confidence using low-code/no-code tools where appropriate.
• Enough coding capability to build or extend solutions when required.
• Experience with LLMs, AI applications or agentic systems, or the aptitude to become highly capable quickly.
• Understanding of security, permissions, governance and production reliability.