Senior Infrastructure Analyst
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Role details
Tech stack
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Job description
You will be there to provide day-to-day operational administration of the Group’s Cyber and AI Lab estate, supporting teaching, research and skills development across cyber security, networking, artificial intelligence and data science curricula.
The postholder will maintain and support virtualised teaching environments, user access, cloud and on-premise lab resources, AI development platforms, and cyber security training systems. They will work closely with curriculum teams and industry partners to ensure that practical teaching environments are available, secure, performant and ready for delivery.
This is a hands-on technical role within a defined operational framework. Platform architecture, strategic design and technical governance remain the responsibility of the Enterprise Architect.
Responsibilities
Cyber Environments
- Administer user and host accounts within lab directory and identity systems.
- Manage user access to cyber security platforms, remote access services and virtual lab environments.
- Maintain account lifecycle processes, including onboarding, offboarding and access reviews.
AI Environments
- Provision and manage access to AI development platforms, notebooks and GPU-enabled environments.
- Support identity integration for AI services and learning platforms.
- Assist in maintaining secure access controls for datasets and model repositories.
Cyber Lab Operations
- Deploy and maintain virtual desktops and cyber security training environments.
- Support virtual machine lifecycle management across lab infrastructure.
- Monitor service availability, capacity and performance.
- Maintain network simulation environments and cyber range assets.
- Support penetration testing, networking and security teaching environments.
- Troubleshoot authentication, connectivity and platform issues affecting students and staff.
AI Lab Operations
- Provision and maintain AI development environments, including Linux-based workstations, notebooks and containerised workloads.
- Support GPU-enabled compute infrastructure used for AI training and inference workloads.
- Maintain AI software stacks and frameworks such as Python environments, Jupyter, TensorFlow, PyTorch and related tooling.
- Assist with deployment of approved AI models and educational resources.
- Monitor GPU, storage and compute utilisation and report capacity concerns.
- Support students and tutors using AI and data science platforms.
Requirements
- Practical Linux administration skills including command-line operation, service management and troubleshooting.
- Understanding of networking fundamentals including TCP/IP, DNS, DHCP and routing concepts.
- Understanding of virtualisation and virtual machine lifecycle management.
- Basic knowledge of cyber security concepts including authentication, access control, vulnerability management and security monitoring.
- Basic knowledge of artificial intelligence and machine learning concepts.
- Familiarity with Python and its use in automation, data analysis or AI workloads.
- Ability to support technical platforms used by students and teaching staff.
- Strong written and verbal communication skills.
Desirable - Cyber
- Familiarity with network simulation platforms such as GNS3, EVE-NG or Packet Tracer.
- Understanding of LDAP, Kerberos and identity management.
- Familiarity with KVM/libvirt or similar virtualisation technologies.
- Awareness of security tooling such as SIEM, vulnerability scanning or penetration testing platforms.
Desirable - AI
- Experience with Jupyter Notebook, Python virtual environments or container technologies.
- Awareness of machine learning frameworks such as TensorFlow, PyTorch or Scikit-Learn.
- Familiarity with GPU computing concepts and NVIDIA technologies.
- Exposure to generative AI, large language models or AI development platforms.
- Understanding of data management, datasets and data governance principles.
Qualifications
Essential
- Level 3 qualification in Computing, IT, Cyber Security, AI/Data Science or equivalent demonstrable experience.
Desirable
- CompTIA Security+
- CompTIA Network+
- Linux+
- Microsoft AI Fundamentals (AI-900)
- Microsoft Azure Fundamentals (AZ-900)
- NVIDIA Deep Learning Institute certification
- Working towards further relevant cyber security or AI certifications
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