AI & Automation Technical Lead Export Finance - G7

Position: AI & Intelligent Automation Technical Lead Export Finance - G7

AI & Intelligent Automation Technical Lead - UK Export Finance - G7

Location: Westminster, London

About The Job

The Digital, Data and Technology (DDAT) directorate has recently been established in UKEF, bringing together digital expertise within the organisation to provide representation of digital services, user‑centred design, analytics and technology at the highest levels. The directorate works closely with all business areas such as the Business Group, Operations and Strategy and Policy. UKEF is committed to improving as a customer‑focussed and led organisation, making it easier for customers to deal with us, offering improved response times, quicker decision‑making and improved case‑processing.

To enable this, UKEF is committed to using digital as a primary means for managing relationships with a wider range of stakeholders. Focusing on developing end‑to‑end services that meet user need and enable business outcomes, this is an exciting new role showing the growth and drive of UKEFs digital ambition.

The AI & Intelligent Automation Technical Lead will work closely with the AI Product Lead and be supported by a multidisciplinary team including user‑centred design (UCD), technology and delivery professionals to ensure cohesive and impactful AI solutions. The role will play a pivotal role in shaping and delivering UKEF’s approach to artificial intelligence, ensuring that AI capabilities are embedded into the organisation’s digital transformation journey.

This role will lead the identification, design and implementation of AI solutions that support strategic objectives, improve operational efficiency and enhance user experience.

This is a leadership role requiring a blend of strategic thinking, technical expertise and stakeholder engagement. The AI & Intelligent Automation Technical Lead will be expected to work with a range of technologies and methodologies, adapting to evolving needs and ensuring that UKEF remains at the forefront of responsible AI adoption.

Job Description

In this role, you will:

Technical Leadership

• Lead the end‑to‑end technical design, development and implementation of AI solutions, including intelligent agents for automation and augmentation.
• Provide technical guidance and mentoring to engineers and analysts working on AI and automation initiatives.
• Document AI architectures, models and agent behaviours to ensure transparency, governance and continuous improvement.

Solution Design & Delivery

• Identify opportunities to apply AI agents (task‑based, conversational, autonomous) to optimise business processes and improve user experiences.
• Evaluate and implement agent orchestration frameworks and multi‑agent systems for complex workflows and adaptive services.
• Integrate AI capabilities with enterprise platforms and services, including low‑code environments, APIs and data pipelines.

Technology Evaluation

• Assess and select appropriate AI models, platforms and tools (e.g. Azure Foundry, OpenAI, Copilot Studio).
• Stay current with emerging AI technologies, particularly developments in agent‑based systems, and evaluate their applicability to UKEF.

Collaboration & Stakeholder Engagement

• Work closely with stakeholders to translate business needs into AI‑enabled solutions, incorporating agent‑based architectures where appropriate.
• Support the training and upskilling of UKEF staff in AI literacy, responsible use of intelligent systems and adoption of AI‑enabled tools.

Governance & Compliance

• Ensure all AI solutions are ethical, secure and aligned with UKEF’s strategic objectives and regulatory obligations.

This list is not exhaustive, and you may be required to carry out additional duties according to business needs.

Person Specification Essential Qualifications

• Graduate‑level education or equivalent experience in AI, Data Science, or Software Engineering.
• Evidence of continuing professional development.

Knowledge

• AI and Machine Learning (A, I)
  • Core principles of supervised, unsupervised and reinforcement learning
  • Model lifecycle management: training, deployment, monitoring
  • Ethical and responsible AI practices, including bias mitigation and explainability
• AI Agents and Agent‑Based Systems (A, I)
  • Understanding of…