At a Glance
- Tasks: Lead the transformation of AI in higher education, creating impactful solutions for students and staff.
- Company: Join Global University Systems, a pioneer in modernising education through AI.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Shape the future of AI in education and make a real difference.
- Qualifications: 6+ years in IT delivery with strong AI/ML experience and leadership skills.
- Other info: Collaborative environment with a focus on ethical AI practices and innovation.
The predicted salary is between 72000 - 108000 £ per year.
Global University Systems is building a modern AI platform to power how our universities recruit, teach, support, and serve students. The Director of AI will lead this transformation, turning promising ideas into production-grade AI solutions that create real value for students and staff. This role owns the AI roadmap end-to-end: from identifying high-impact use cases, to running rapid experiments, to scaling successful solutions across multiple Higher Education Institutions.
What you’ll do:
- Set vision and strategy: Own and continually refine the AI initiatives portfolio and roadmap for the group. Run a structured intake process for new ideas, assessing value, feasibility, data readiness, ethical risk, and compliance. Define clear success measures for every proof of concept (PoC) and MVP, including KPIs, leading indicators, and decision gates to continue, pivot, or stop.
- Lead PoCs and MVPs: Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers, Solution Architect, and domain experts from Admissions, Registry and Student Services. Design experiments, test hypotheses, and iterate quickly, ensuring human-in-the-loop for critical decisions such as admissions triage or student risk flagging. Embed Responsible AI practices from the start, including bias assessment, explainability, accessibility, documentation, and impact assessments tailored to higher education.
- Scale platforms and solutions: Take validated MVPs into production with robust architecture, integration patterns, security controls, SLAs, and operational runbooks. Establish MLOps across the university environment, including model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g., orchestration, RAG services, prompt safety, connectors) that support multiple domains such as Recruitment & Admissions, Student Records & Registry, Timetabling & Operations, Teaching & Learning, Student Support & Wellbeing, and Research Administration. Coordinate integrations with core systems including SIS (e.g., Banner, Workday Student), LMS/VLE (Moodle, Canvas), CRM (Salesforce), library systems, HR/Finance (ERP), and identity platforms (e.g., Azure AD).
- Govern AI responsibly: Implement a practical AI governance framework that includes a use case register, risk scoring, impact assessments, model documentation, and audit trails. Ensure compliance with GDPR, accessibility standards (e.g., WCAG), information security policies, and emerging AI regulations. Define and enforce guardrails for data and GenAI use: data access controls, PII handling, prompt/data leakage prevention, and content moderation.
- Drive adoption and change: Partner with Deans, Registry, Admissions, Student Services, IT, Legal and other stakeholders to align on priorities and rollout plans. Communicate progress through clear dashboards and storytelling, highlighting wins and lessons learned to build momentum. Prepare teams and students for AI adoption with training, standard operating procedures, ethical use guidelines, and tailored communications.
- Manage vendors and financials: Lead RFPs and SOWs for AI vendors, data providers, and implementation partners, including evaluation of cost, performance, and scalability. Track and optimize cloud and AI platform spend, balancing cost with value; negotiate campus-wide licensing where beneficial.
What you bring:
- Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Business Analytics, or a related discipline.
- Knowledge and skills: Product and outcome mindset; delivery excellence; technical fluency; responsible AI and data literacy; change leadership; experience with major cloud and AI stacks such as Azure OpenAI / OpenAI, Azure ML, Databricks, Kubernetes, and Docker; familiarity with data platforms such as Azure Data Lake, Synapse/ADF, Delta Lake, and messaging platforms; exposure to MLOps and observability tools; knowledge of integrating with SIS, LMS, CRM, ERP, and IdP; comfort with collaboration and reporting tools.
- Experience: 6+ years in IT delivery, product, or program leadership roles, including at least 3 years leading AI/ML or advanced analytics initiatives end-to-end. Proven track record running Agile PoCs and MVPs and scaling them into production within complex organizations. Strong understanding of AI/ML techniques, data pipelines, APIs, and microservices. Hands-on experience with cloud platforms and MLOps tools plus observability practices. Familiarity with higher education processes and integrations across SIS, LMS, CRM, and ERP environments. Knowledge of data privacy, accessibility, security, and Responsible AI in academic or similarly regulated contexts. Excellent stakeholder communication skills. Experience designing or operating an AI platform or shared AI services used across multiple domains or business units. Hands-on work with vector databases and retrieval pipelines and guardrails for GenAI. Background in enterprise architecture and integration patterns. Relevant certifications.
If you are excited by the opportunity to shape the future of AI in higher education and deliver impact at scale, we encourage you to apply and join us on this journey.
AI Director in Nottingham employer: Top End jobs
Contact Detail:
Top End jobs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Director in Nottingham
✨Tip Number 1
Network like a pro! Connect with folks in the higher education and AI space on LinkedIn or at industry events. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those related to AI and education. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on Agile methodologies and AI concepts. Be ready to discuss how you've led projects from idea to production, and don’t forget to highlight your experience with cross-functional teams!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission to transform higher education with AI.
We think you need these skills to ace AI Director in Nottingham
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with AI and leadership in tech. We want to see how your skills align with our mission to transform higher education through AI.
Showcase Your Impact: When detailing your past roles, focus on the measurable outcomes you achieved. Use specific examples of how you've led AI initiatives or improved processes, as we love seeing tangible results!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and ensure your key achievements stand out. Remember, less is often more!
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at Top End jobs
✨Know Your AI Stuff
Make sure you brush up on the latest AI trends and technologies relevant to higher education. Be ready to discuss specific AI techniques like NLP or classification, and how they can be applied to improve student services or recruitment processes.
✨Showcase Your Leadership Skills
As a potential AI Director, you'll need to demonstrate your ability to lead cross-functional teams. Prepare examples of how you've successfully managed diverse groups in past projects, especially in Agile environments, and how you’ve driven adoption of new technologies.
✨Prepare for Ethical Discussions
Given the emphasis on Responsible AI, be ready to talk about ethical considerations in AI deployment. Think about how you would address bias, data privacy, and compliance with regulations like GDPR in your strategies.
✨Have a Vision Ready
Articulate your vision for AI in higher education clearly. Think about high-impact use cases you would prioritise and how you would measure success. This will show that you’re not just technically savvy but also strategic in your thinking.