This is a newly established role, to design and lead the Group of Companies in-house AI-enabled software delivery capability, and to drive the Intranet rewrite in phase 1 and its ongoing enhancement. You will be writing code yourself while also building the development function and the way it works day-to-day. This is a player and coach role. The initial focus is the Intranet — a platform that underpins key operational workflows across the credit business. The rewrite will be phased to a modern stack, designed alongside business heads, and judged on whether it actually improves how work gets done, with the aim to extend it across the other companies in the Group. Over time, you will grow and lead a small engineering team that takes on more of our workflow automation and internal application development.

Key Outcomes

• A working, repeatable delivery approach with predictable planning, releases, testing, documentation, and operational support.
• A modernised Intranet delivered in phases, with the credit business heads involved throughout and measurable improvement in how teams work.
• A secure and governed AI-assisted delivery workflow that improves speed without compromising quality, confidentiality, or maintainability.
• An in-house development function with clear tooling, engineering standards, onboarding, and shared knowledge ready for future growth.

Reporting Line and Scope

This role reports directly to the Group CEO. This is a newly established, position — AI adoption is a new and strategically material area for the Group and its business, and the person leading it needs direct access to the Group CEO on priorities, budget, and how the team is shaped. The Group CEO coordinates with the Group CFO and the Board on the role’s mandate and ongoing performance. Day-to-day operational coordination with IT sits with the IT Manager.

The role holder prepares and delivers a formal quarterly AI adoption and delivery report for Board review, coordinated through the Group CEO.

The role has commercial authority over the AI tooling budget and the contracted development house, within limits approved by the Group CEO and Group CFO.

Core Responsibilities

1. Engineering Function Design and Orchestration

• Set up the development department from scratch — how the team works and at what pace.
• Put the delivery infrastructure in place: source control, environments, releases, testing, documentation, and support.
• Decide how prioritisation, change control, quality gates, and risk management work in practice.
• Make architecture and delivery calls on your own, explain the reasoning, and avoid over-engineering.

2. Hands-On Delivery Using Coding and AI-Assisted Workflows

• Build things yourself, whether by writing the code or by directing AI tools and checking what they produce.
• Turn what the business needs into software that is secure, safe to run, and someone else can pick up later.
• Get prototypes in front of people fast, then tighten them up with testing and review before they go live.
• Hold the contracted development house to the same delivery and quality standards set for in-house work.

3. Business Partnering and Solution Design

• Sit with business heads, work through how their processes actually run today, and build the systems to match.
• Run workshops, write down what we’re actually building, and be honest with people about what won’t fit in this round.
• Keep shipping improvements, and let the value they create decide what comes next.

4. Player and Coach Leadership

• Bring the junior developers along — pair with them, review their code, and talk regularly about what they want to learn next.
• Run the team so people take responsibility for what they build and move at a real pace.
• Write things down so the business isn’t stuck if one person is out.

5. Responsible AI and Governance

• Follow company policy on how AI tools are used, what data they touch, and what stays out of them, including data classification and prompt hygiene.
• Ensure all AI-assisted work is reviewed and validated by a human before release.
• Keep records of what AI was used for and what it produced, so we can go back and check.
• Own the AI tooling budget — pick what we use, watch how much it gets used, and keep spend within the approved limit.
• Prepare the quarterly AI adoption and Board feedback report, coordinated through the Group CEO.

Required Qualifications and Experience

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or equivalent demonstrated through career progression.
• Postgraduate qualification is advantageous.
• Formal AI-related training or certification is advantageous (e.g. applied machine learning, generative AI, or responsible AI programmes).

Work Experience

• At least seven years writing software, with demonstrable hands-on delivery across the full lifecycle, and work you’ve actually shipped end to end.
• Experience setting up — or seriously fixing — how an engineering team works, not just stepping into something that already runs.
• A track record of leading delivery while still writing code yourself.
• Proven, commercial deployments of AI-assisted software delivery in production environments, with references or demonstrations available — not side projects.
• Experience working with business stakeholders to redesign processes and deliver workflow automation.
• Experience in financial services or another regulated environment is advantageous.

Key Competencies

• Makes architecture and delivery calls on your own and can explain why, without needing a committee behind you.
• Can move forward when the requirements aren’t clear yet, while still managing risk and documenting decisions.
• Reaches for the simplest thing that works and pushes back when something is being over-engineered.
• Strong engineering judgement, with genuine weight given to security and maintainability, not just delivery speed.
• Can talk to the business and to other engineers, and knows when to change register.
• Happy in a small company, where there’s no specialist team waiting downstream and the task is yours from start to finish.

Success Measures

What success looks like in the first 6–12 months

• A delivery approach that works week to week, so planning and releases stop being a surprise.
• A modernised Intranet, delivered in phases, with business heads involved throughout and visible improvement in how teams work.
• An AI-assisted way of working that speeds us up without creating quality or confidentiality problems.
• A small development function with clear tooling, documented standards, and onboarding ready for future growth.
• A productive relationship with the contracted development house, with ‘the way’ incorporated into how they work with us.
• Department heads see the role as a genuine enabler of AI and automation across the business.