Principal AI Engineer


Company:	Government Recruitment Service
Salary:	from £59,816 a year
Hours:	Full-time
Location:	Hastings
Working pattern:	Hybrid - 2 days remote
Job type:	Permanent
Posting date:	4 Nov 2026
Closing date:	15 Nov 2026

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Summary

Do you want to develop impactful AI products that address real-world transport challenges?

Are you an innovator who is driven to implement AI within DfT to support our business and responsibly deploy it across the transport system to improve transport user experiences and boost growth?

Then we’d love for you to apply for this job!

We’re looking for Principal AI Engineers to lead the technical delivery of innovative, well-designed solutions that inform high-stakes decisions, transform complex processes and operations, and support critical policy objectives.

You will use your technical expertise to design, build, deploy, and maintain AI solutions – providing technical ownership through all phases of the product lifecycle. This involves effectively collaborating with colleagues within DfT, across government and with external partners.

Our Team

You will join the AI and Data Science Team, which owns the technical development of AI products and solutions in DfT’s AI Programme. Our AI Programme is split across five G6-led partner team(s): AI and Data Science own the technical development of AI and data science products (i.e., where this role sits); Human Centred AI design and implement social, behavioural and user research; Strategy, Governance and Responsible Adoption; and Transport sector AI Policy. We are also supported by the Problem Structuring and Analysis team. Our teams work together very closely.

As demand for our work has grown, we are now looking for new members to join us!

Essential requirements

You will need to have experience of: Leading the end-to-end technical delivery of impactful AI or data science products, including design, development, deployment, monitoring, assurance, incident response and continuous improvement in production environments (lead criterion). Programming and software engineering to design and develop high-quality, scalable and maintainable solutions, applying strong engineering practices including version control, testing and code review. Deploying and managing products across development, test, and production environments on cloud platforms (e.g., GCP/AWS), using CI/CD pipelines with automated testing and Terraform or similar infrastructure-as-code (IaC) tools to ship changes safely, reproducibly, and with rollback. Applying a range of AI technologies, such as LLMs, VLMs, RAG, Agents, MCP, computer vision, GraphML, recommendation systems or reinforcement learning. Collaborating across multidisciplinary teams, translating organisational priorities into technical solutions, communicating complex information effectively, and helping build organisational capability through setting standards, coaching and establishing reusable engineering practices. Statistical evaluations of AI and data science solutions using appropriate designs and datasets, applying lessons from research and practice. Considering ethics and legislation when developing AI and data science solutions e.g., GDPR, design of appropriate human oversight in AI tools. It is highly desirable that you have hands-on experience in one or more of the following: Using your credibility and expertise in AI architecture to advise and challenge colleagues on architecture design choices, ensuring proposals align with the organisation's technology landscape and strategy, establishing reusable patterns and working closely with the DfT Architecture team to support proposals through technical governance processes. Maintaining multiple AI products in production using MLOps practices, including monitoring, versioning, automated evaluation and CI/CD. Building and deploying agentic services using enterprise platforms such as Copilot and Gemini Enterprise, integrating backend services, APIs and organisational data to deliver secure, scalable solutions at pace. Red teaming AI products using off-the-shelf tools and custom-built tests to systematically uncover vulnerabilities and failure modes such as prompt injection, jailbreaks, data leakage, harmful outputs, and misaligned behaviour, and implementing effective mitigations. Building intuitive, front-end interfaces that users love. Training, fine-tuning and deploying models for specialist tasks.

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