Lead technical architect, AI Centre of Excellence (up to 95,278)

As a lead technical architect, you will be designing and building AI-based products and services for a diverse set of internal and external users.

The Department for Education (DfE) have developed an AI Centre of Excellence (CoE) to facilitate the adoption of AI across the DfE. The objectives of the CoE are:

1. To facilitate the delivery of AI projects and tools.
2. Develop and maintain the core technologies and platforms for AI.
3. To provide guidance and advice for the secure development and use of AI technologies.
4. To build skills and capability for the effective development and use of AI technologies.
5. To have oversight of all AI projects within the Department for effective assurance and reporting.

There is a need to support the ongoing development of the CoE service for building and integrating AI solutions into DfE products and services.

The post holder will develop designs and patterns for AI use cases, develop and publish standards, and provide technical guidance for delivery of AI work across the DfE. This will involve engagement both within the CoE and across teams in the Department, to ensure the safe and effective development and use of AI technologies.

To enable delivery of new products, the postholder will also help shape data strategy and lead complex technical projects by effectively using data to uncover insights, build models and support decision-making for AI use cases.

Your main responsibilities will include:

• Designing and maintaining the AI CoE service and products - keeping up to date with the latest technologies, whilst delivering software early and often.
• Leading technical specialists across multiple AI projects and services, on problems that require broad architectural thinking.
• The development of designs, patterns and technical guidancefor new AI use cases
• Using data to uncover insights, build models, and support decision-making for AI use cases
• Defining how to build and operate user-centred, open-source web systems in an agile environment, to serve a variety of citizen and government needs.
• Being responsible for the technical design and development of AI products and services, including how they interact with their surroundings, and how they evolve over time.
• Challenging entrenched practices and influencing decision-makers, looking for deeper underlying problems to solve, and larger opportunities for digital transformation (including AI and productivity).
• Communicating the vision for the AI CoE and AI services to developers and non-developers alike, working in multi-disciplinary teams that bring policy and delivery together.
• Playing an active role in the DfE Technical Architecture community, where you will share knowledge of tools and techniques, as well as joining related communities of practice and events where appropriate, such as product, user research, design, platforms, security, etc.
• Helping to build a diverse, inclusive culture across the technical architecture community.

Essential Criteria:

Assessed in application and both interview stages experience in:

• Leading multidisciplinary teams to design and deliver AI-enabled, user-centred services in an agile environment.
• Establishing engineering practices for AI systems, including TDD, CI/CD, automated deployment, model lifecycle management, version control (Git) and DevOps.
• Designing and assuring scalable, secure, cloud-based AI architectures, including data platforms, model hosting and integration patterns.
• Software development experience building production AI systems, including .NET and Python, developing and integrating ML/GenAI components via APIs, and applying testing, security and observability practices.
• Knowledge of open-source principles and technologies.

Assessed in application and second interview stage:

• Ability to build consensus between diverse and often conflicting interests, working with technical and non-technical stakeholders to achieve agreement on AI architectures, standards and patterns.
• Ability to take a strategic, whole-system view of AI solutions, considering data, platforms, integration, governance and long-term sustainability.
• Practical understanding of end-to-end technical architecture, from front-end and APIs, to data pipelines, model layers, infrastructure and networking.

The following criteria are desirable. Applicants evidence against these criteria will be used at interview in the event of a tie break situation, to make an informed decision:

• Experience implementing automated testing and evaluation for AI systems (e.g. model validation, prompt evaluation, continuous assurance).
• Experience applying the UK Government Service Standard, Technology Code of Practice, and secure-by-design principles.
• Experience mentoring and developing AI engineering and architecture capability in multidisciplinary teams.
• Ability to work with stakeholders to produce effective strategies for technology choices, using the most appropriate languages, frameworks and tools to meet user and business needs.