Technical Lead – AI & Software Engineering - 7720

Job Title: Technical Lead – AI & Software Engineering

Salary: £53,100 - £70,950

Location: Cambridge, UK - Hybrid (at least 2-3 days per week in the office)

Contract: Permanent

Hours: Full-time, 35 hours per week

We are recruiting a Tech Lead for each of two projects. Each Tech Lead will work within a POD led by the Technical Product Manager for their project, reporting to the Solutions Lead.

We are Cambridge University Press & Assessment, a world-leading academic publisher and assessment organisation and a proud part of the University of Cambridge.

About the role

We're seeking a hands-on Tech Lead with strong leadership and collaboration skills to lead delivery of AI-enabled solutions that transform how assessments are created and marked. Your solutions will depend on privately hosted language models, and you'll ensure they are secure, reliable, auditable and grounded in approved assessment content, working within the enterprise direction set by the Solution Lead.

In this role, you will not only lead and mentor a small cross‑functional squad, but also remain deeply involved in the technical delivery—applying your expertise directly to architect, code, and implement solutions. You will set technical standards, write and review code, and solve complex challenges alongside your team, taking a first release from idea to live use by assessment experts and examiners. Throughout, you'll work closely with those experts, who remain in control of every decision that affects a candidate. We are looking for someone who leads by example, demonstrates recent hands‑on experience of building products with language models, and is passionate about both technical excellence and team development.

• Content Creation: AI‑assisted solutions that help to transform the authoring and quality assurance of assessment content, including question papers and mark schemes.
• Marking and Core Operations: AI‑assisted tools that support examiners in reading handwritten scripts and marking consistently, with examiners making every decision.

Additional responsibilities and accountabilities include:

• Deliver AI‑Enabled Solutions: Build end‑to‑end products that use securely hosted language models, from data and retrieval through to user interfaces and integration with existing assessment systems, while communicating design rationale to diverse stakeholders for buy‑in and feedback.
• Ground and Validate Outputs: Use retrieval over approved assessment content, structured outputs and rule‑based validation so that results are accurate, traceable and consistent with syllabus requirements, working with assessment experts owners to agree what “correct” looks like.
• Measure Quality: Build evaluation sets and quality gates alongside assessment experts, using them to select and compare models and to show each release is fit for use, fostering a team culture of shared accountability and continuous improvement.
• Keep Experts in Control: Design review workflows with examiners and assessment experts so they make every final decision, with every AI suggestion and human decision recorded for audit.
• Protect Sensitive Content: Champion secure practices aligned with industry standards, ensuring models, data, prompts and logs stay within approved secure environments, and influencing stakeholders to prioritise security in decision‑making.
• Shape Cloud‑Native Architecture: Design scalable, resilient architectures on AWS using approaches like microservices, serverless, containerisation and GPU‑based model hosting, using Infrastructure as Code for cost‑effective, repeatable deployments.
• Drive Observability: Implement robust observability covering system performance, reliability and the quality of AI outputs, so issues are found and resolved proactively.
• Integrate with our Enterprise Platforms: Design solutions that integrate with our event‑driven exam processing platform and with content management and item banking systems, collaborating with cross‑functional groups to keep solutions decoupled and scalable Build Web‑App Solutions: Develop responsive, high‑performance web applications that make assessment experts and examiners faster and more confident, adapting to user feedback and business priorities through iterative collaboration.
• Lead Automation and CI/CD: Drive automation through CI/CD pipelines to accelerate delivery and minimise technical debt, promoting agile ways of working that encourage team input and adaptability.
• Mentor and Collaborate: Guide engineers, foster a culture of learning and inclusivity, and collaborate with Technical Product Manager for their project , the other project team, platform and schema owners, and the Solution Lead so that shared components and formats stay consistent.
• Facilitate Stakeholder Engagement: Act as a key liaison in stakeholder groups, translating technical concepts including what AI can and cannot reliably do into actionable insights, resolving conflicts, and building consensus to ensure project success.

This position has been classified as a hybrid role, requiring the selected candidate to typically spend 40‑60% of their time collaborating and connecting face‑to‑face at their dedicated location. Aside from our hybrid principles, other flexible working requests will be considered from the first day of employment, including other work arrangements should you require adjustments due to a disability or long‑term health condition.

About You

As a hands‑on Tech Lead, you'll bring broad expertise in cloud‑native architecture and in building products that depend on language models, coupled with exceptional soft skills to thrive in collaborative environments. Your experience includes taking AI‑enabled solutions into production, with a realistic understanding of their strengths, limitations and failure modes, and a focus on horizontal skills like problem‑solving, adaptable design thinking, and leading through influence. You excel in agile, cross‑functional teams, where your ability to communicate effectively, mentor diverse groups, and work alongside domain experts is as critical as your technical acumen. You will be expected to apply your technical skills directly—writing code, architecting systems, and solving complex technical challenges alongside your team.

• Leadership and Mentoring: Proven track record of guiding teams, fostering collaboration, and promoting a growth mindset to unlock team potential.
• Communication and Stakeholder Management: Skilled at articulating complex technical ideas to non‑technical audiences, setting realistic expectations about AI, facilitating workshops, and building relationships to align on shared goals.
• Working with Domain Experts: Comfortable treating assessment experts and examiners as the owners of quality, turning their judgement into clear acceptance criteria and evaluation measures.
• Adaptability and Collaboration: Thrive in dynamic settings, adapting to evolving priorities and a fast‑moving AI landscape while collaborating across functions to drive innovation and resolve challenges.
• Problem‑Solving and Resilience: Approach issues with a holistic, user‑centred mindset, balancing technical feasibility with business impact.

On the technical side, you'll have hands‑on experience of building products with large language models, including retrieval over domain documents, structured or schema‑constrained outputs, evaluating output quality against expert judgement, and running models in private or self‑hosted cloud environments. You'll also bring proficiency in areas like microservices, serverless, containerisation, and building web applications, with experience in observability, security standards, Infrastructure as Code, and CI/CD practices. We value transferable skills over specific