UK

United Kingdom · Research and development · Principal/Manager (12-16 years)

Global Research Infrastructure Director

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  • Experience bandPrincipal/Manager (12-16 years)
  • Direct reports3-8 reports
  • Reports toDirector, Global Research Infrastructure
  • UK framework levelUsually someone running a function, or a director

Also advertised as Head of Research Computing · Senior Manager, R&D IT · Principal Research Systems Lead · Associate Director, Scientific Computing

Built on 43,079 real UK job descriptions we analysed · grounded in what real qualifications cover

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

OTHM Level 7 Diploma in Data Science OTHM Qualifications · Level 7 · covers 2 of 8 standards
Level 6 Award in Data-led Decision Making Institute of Sales Professionals · Level 6 · covers 1 of 8 standards
Level 6 Certificate in Professional Sales Institute of Sales Professionals · Level 6 · covers 1 of 8 standards
Level 6 Diploma in Professional Sales Institute of Sales Professionals · Level 6 · covers 1 of 8 standards
TQUK Level 6 Diploma in Digital Leadership (RQF) Training Qualifications UK Ltd · Level 6 · covers 1 of 8 standards
NOCN Level 4 certificate for Data Analysts NOCN · Level 4 · covers 3 of 8 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Data Science Foundations OTHM Level 7 Diploma in Data Science
Data-led Decision Making Level 6 Award in Data-led Decision Making
Data science TQUK Level 6 Diploma in Digital Leadership (RQF)
Data Visualisation NOCN Level 4 certificate for Data Analysts

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
Frontier Fluency the next wave, beyond mainstream AI
Trust Fluency keeping the digital world safe
Your Plan Illustration

Built for Global Research Infrastructure Director

4 units that map to this job, from the qualifications that cover it.

  1. Data Science Foundations OTHM Qualifications · covers 2 of 8 standards Level 7
  2. Data-led Decision Making Institute of Sales Professionals · covers 1 of 8 standards Level 6
  3. Data science Training Qualifications UK Ltd · covers 1 of 8 standards Level 6
  4. Data Visualisation NOCN · covers 3 of 8 standards Level 4
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Global Research Infrastructure Director?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

  • AI Strategy & Governance for Research
  • Quantum Computing Readiness
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Global Research Infrastructure Director plan as you set up, starting with the free Automation Fluency module. No card.

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3What this role really is

This job involves building and running the computing, storage and lab systems that scientists rely on for research. It means planning infrastructure and managing the people who keep it running.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

HPC & Workload Mgmt (Slurm, SGE, AWS ParallelCluster, Azure CycleCloud) Strategic

Leading platform decisions (e.g., on-prem vs. cloud burst), modelling TCO for HPC solutions, and setting policies for workload management across the global research estate.

Lab Informatics (Benchling, LabWare, Dotmatics, Scilligence) Strategic

Owning the enterprise lab informatics roadmap, selecting and negotiating contracts for next-gen platforms, and ensuring GxP compliance for all lab systems.

Storage Systems (NetApp, Isilon, AWS S3/Glacier, Azure Blob) Strategic

Developing the global data storage and sovereignty strategy, approving multi-million pound storage hardware refresh cycles, and defining data lifecycle policies.

Infrastructure as Code (Terraform, Ansible) Advanced

Mandating and governing the use of IaC across all R&D infrastructure to ensure reproducibility, compliance, and efficient deployment of environments. You'll review and approve major IaC changes.

Data Pipeline Tools (Nextflow, Snakemake) Intermediate

Setting standards for scientific workflow management, ensuring scalability and reusability of analysis pipelines across the organisation, and understanding their resource consumption.

Financial/GRC Platforms (Anaplan, ServiceNow GRC) Expert

Using Anaplan for CapEx/OpEx budget planning and forecasting, and leveraging ServiceNow GRC to manage system validation, compliance documentation, and audit trails for regulated systems.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Budget Allocation (CapEx/OpEx) Escalate all budget requests to supervisor for review and approval. Propose budget items for specific projects; requires manager approval. Own project budgets up to £50K; recommend larger investments to leadership.
Technology Selection & Architecture Execute tasks using specified tools and configurations. Select appropriate tools from an approved list for routine tasks; propose minor architectural improvements. Design and implement technical solutions within project scope; recommend new technologies for evaluation.
Team Management & Organisational Design No direct reports; focus on individual contribution. Informal guidance to new joiners; no hiring/firing authority. Mentor 0-2 junior team members; provide input on performance reviews.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Research Computing TCO Reduction
Total Cost of Ownership for your specific infrastructure domain (e.g., HPC, Lab Informatics). This includes CapEx, OpEx, and cloud spend.
Target · Reduce TCO by 10% year-on-year without impacting research output.

Optimising cloud resource allocation and negotiating better vendor contracts led to a £750K saving this year, bringing TCO down by 12%.

Key Scientist Stakeholder Satisfaction
How happy our principal investigators and research leads are with the infrastructure and support provided by your team.
Target · Achieve >85% satisfaction score in annual surveys.

After implementing a new HPC scheduling policy, the 'Slurm Queue Wait Time' feedback improved from 'frustrating' to 'acceptable', reflected in an 88% satisfaction score for HPC users.

Infrastructure Budget Adherence
How closely your actual spending aligns with your approved CapEx and OpEx budgets.
Target · Align infrastructure budget to within 5% of forecast.

Managed a £1.2M CapEx budget for the new storage array project, coming in at £1.18M (1.6% under budget) by careful vendor negotiation.

Research Data Processing Time Reduction
The average time it takes for critical scientific data (e.g., genomic sequencing, imaging) to be processed through our pipelines.
Target · Reduce average processing time by 15% through strategic platform upgrades.

Upgrading the InfiniBand network in our HPC cluster cut the average time for large-scale genomic analysis pipelines from 48 hours to 39 hours, a 18.75% improvement.

Strategic Influence & Roadmap Clarity
Your ability to define and communicate a clear, compelling multi-year roadmap for your infrastructure domain, and to get buy-in from R&D leadership.
  • Roadmap is regularly reviewed and adopted by R&D VPs. Your proposals are seen as well-reasoned and proactive. You're invited to early-stage scientific planning meetings to provide infrastructure input.
Team Development & Retention
How effectively you build, mentor, and retain a high-performing team of engineers and architects.
  • Low voluntary attrition rates in your team. Your direct reports are actively developing new skills and taking on more responsibility. You've successfully promoted at least one team member in the last 12-18 months. Positive feedback in 360-degree reviews regarding your leadership and coaching.
Proactive Problem Solving & Risk Mitigation
Your knack for spotting potential issues (technical, budgetary, compliance) before they become major problems, and putting plans in place to address them.
  • You regularly present identified risks and proposed mitigation strategies to leadership. Fewer 'surprise' outages or budget overruns. You're seen as the person who thinks three steps ahead on infrastructure challenges.
Compliance & Audit Readiness
The consistent 'validated state' of your GxP-regulated systems and your team's ability to sail through internal and external audits.
  • Zero critical findings in audits related to your infrastructure domain. All system validation documentation is up-to-date and easily accessible. Your team consistently follows change control procedures for regulated systems.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Enabling Scientific Breakthroughs

You get a genuine kick out of seeing your infrastructure directly contribute to a new discovery or a faster drug development cycle. Knowing your work helps scientists unravel complex biological problems is a huge driver.

Watching a new gene sequencing run complete in record time because of the HPC cluster you helped design and seeing the excitement from the research team.

Solving Complex Organisational Problems

You thrive on untangling technical, financial, and political knots to deliver a solution. This isn't just about servers; it's about navigating people, budgets, and processes to achieve a strategic goal.

Successfully migrating a legacy lab system to a modern cloud platform, overcoming resistance from long-term users and tight budget constraints.

Building and Leading High-Performing Teams

You enjoy coaching, mentoring, and developing your team members, helping them grow their skills and take on bigger challenges. Seeing your team succeed is a major source of satisfaction.

A junior engineer you mentored successfully leads a complex instrument integration project from start to finish, exceeding expectations.

What frustrates people
  • Having to explain to Finance for the fifth time why a single server with 8 A100 GPUs costs more than a small house and is absolutely necessary for our AI-driven drug discovery programme.
  • Discovering a Principal Investigator has been running a multi-million pound research programme on a powerful workstation stored in a dusty closet, with no backups or security, creating a massive data risk.
  • The constant tension between researchers who demand admin rights to install any obscure scientific software they find and the security team who wants to lock everything down to GxP standards.
  • Being blamed for project delays when, in reality, the scientific code being run is poorly written, incredibly inefficient, and consumes 100x more resources than it should, bottlenecking the entire cluster.
  • Fighting the 'not invented here' syndrome from computational scientists who genuinely believe they can build and manage enterprise-grade infrastructure better than your dedicated team.
  • Dealing with legacy scientific instruments that only run on an unsupported Windows XP machine, which is a massive security hole but is critical to an ongoing, regulated study.
  • The end-of-quarter scramble to spend CapEx budget before it's lost, often leading to rushed purchasing decisions that aren't always optimal.
  • The sheer volume of 'urgent' requests that turn out to be 'important, but not actually urgent' once you dig into them, constantly disrupting your planned work.
What this role does not give you
  • A purely technical, hands-on coding or engineering role; you'll be managing people and strategy more than building things yourself.
  • A predictable, stable environment where requirements rarely change; expect constant shifts and new challenges.
  • A role where you can avoid difficult conversations or political navigation; influencing stakeholders is central to success.
  • Instant gratification on every project; infrastructure changes often have long lead times and complex dependencies.

8Who you work with

This role directly underpins the entire R&D pipeline. Your decisions on infrastructure strategy, capacity, and compliance directly influence the speed, cost, and regulatory integrity of our scientific programmes. Get it right, and we're faster, more efficient, and more innovative. Get it wrong, and we face delays, budget overruns, and potentially critical compliance failures.

Inside the business
  • R&D Leadership (VPs, Heads of Research)
  • Principal Investigators and Research Scientists
  • Finance Department (for budget approvals)
  • Security & Compliance Teams
  • Enterprise IT Leadership
  • Procurement Department
Outside the business
  • Key Technology Vendors (e.g., Dell, NetApp, AWS, Benchling)
  • Industry Consortia and Research Collaborators
  • Regulatory Auditors (e.g., MHRA, FDA)

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • At least 5 years of experience leading complex research infrastructure projects or managing a team of engineers/architects in a regulated R&D environment.
  • Proven track record of managing significant CapEx and OpEx budgets (e.g., £500K+).
  • Demonstrable experience with GxP compliance and system validation (CSV) in a life sciences context.
  • Strong understanding of HPC architectures, cloud computing for scientific workloads, and enterprise storage solutions.
  • Excellent communication and influencing skills, capable of engaging with both deeply technical teams and non-technical executive leadership.
  • A degree in Computer Science, Engineering, or a related scientific field, or equivalent practical experience.

10What to practise next

Where the job is going, and what to do about it starting this week.

Advanced Cloud Native Architectures for Scientific Workloads

The shift to cloud-native isn't just about VMs; it's about serverless, containers, and managed services. You'll need to architect and govern these complex, often ephemeral, environments to ensure cost-effectiveness, scalability, and compliance for scientific applications.

Kubernetes & Container Orchestration · Serverless Computing for Data Processing · Managed Database Services for Research · Multi-Cloud & Hybrid Cloud Strategy

  • This quarter: Review your team's current cloud architecture for one major research project; identify areas for cloud-native optimisation.
  • Next 6 months: Lead a proof-of-concept for a serverless data processing pipeline.
  • Next 12 months: Develop a multi-cloud strategy document for R&D leadership.
  • Ongoing: Encourage your team to pursue advanced cloud certifications and share learnings.

Quick win: Identify one 'rogue IT' cloud project and work with the team to bring it into a governed, cost-optimised cloud-native architecture.

Data Mesh & Data Product Governance

As scientific data proliferates, centralising everything becomes a bottleneck. The data mesh paradigm, where data is treated as a product owned by domain teams, offers a way forward. You'll need to define the infrastructure and governance for this decentralised approach.

Domain-Oriented Data Ownership · Data Product Definition & Discovery · Self-Serve Data Infrastructure · Federated Data Governance

  • This quarter: Read 'Data Mesh' by Zhamak Dehghani and discuss its applicability with your team.
  • Next 6 months: Identify one research domain to pilot a data product approach, defining the infrastructure needed.
  • Next 12 months: Develop a proposal for a federated data governance model for R&D data.
  • Ongoing: Collaborate with data science and research teams to understand their evolving data access and sharing needs.

Quick win: Map out the current data flow for a complex research project, identifying bottlenecks that a data mesh approach could solve.

11Staying current once you are in

What people here do to keep up
  • Regularly attend industry conferences (e.g., SC Conference for HPC, Bio-IT World for life sciences IT) to stay abreast of emerging technologies and network with peers.
  • Participate in relevant professional organisations or consortia focused on research computing or GxP compliance in life sciences.
  • Engage in continuous learning through online courses, webinars, and technical publications to deepen knowledge in cloud-native architectures, AI/ML infrastructure, and advanced data management.
  • Seek out leadership and management training programmes to further develop your people management, strategic planning, and executive communication skills.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

AI Strategy & Governance for Research

AI is no longer just a tool; it's becoming a core methodology in research. You'll need to move beyond simply providing GPU resources to actively shaping how AI is used, governed, and scaled across R&D, ensuring ethical use and data privacy.

  • AI Model Lifecycle Management
  • Ethical AI & Bias Mitigation
  • Data Privacy & Security for AI/ML
  • AI Hardware Acceleration Trends

Quantum Computing Readiness

While still nascent, quantum computing holds immense potential for complex scientific problems. You won't be building quantum computers, but you'll need to understand its implications for data storage, security, and the future compute landscape, preparing the organisation for its eventual impact.

  • Quantum Algorithms for Research
  • Quantum-Safe Cryptography
  • Hybrid Quantum-Classical Architectures
  • Quantum Computing as a Service (QCaaS)

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • GxP Compliance & System Validation (CSV)
  • HPC Architecture & Optimization
  • FAIR Data Principles Implementation
  • Scientific Data Lifecycle Management
  • Capital Expenditure (CapEx) Planning & Justification
  • Cloud FinOps for Research

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Lead Research Infrastructure Architect (L4)

    3-5 years in this role

    Skills to master

    • Deep technical architecture for complex systems, setting technical standards, influencing technical direction without direct authority, early-stage mentoring.

    You're ready to move on when

    • Successfully designed and delivered 2-3 multi-system infrastructure solutions that significantly improved research capabilities.
    • Consistently sought out for technical guidance by peers and senior leadership.
    • Demonstrated ability to mentor junior engineers and lead project teams effectively.
    • Proactively identified and mitigated significant technical risks on major projects.
  2. 2

    Senior Manager, Enterprise IT Infrastructure (from another department)

    4-6 years in a similar management role

    Skills to master

    • People management, budget ownership, vendor relations, strategic planning. You'd need to quickly gain deep domain knowledge in research-specific infrastructure (HPC, LIMS, GxP).

    You're ready to move on when

    • Managed a team of 5+ technical professionals and a budget of £1M+.
    • Successfully delivered large-scale infrastructure projects in a complex enterprise environment.
    • Demonstrated strong leadership, communication, and stakeholder management skills.
    • Shown a keen interest and aptitude for learning the specifics of scientific computing and regulated environments.
  3. 3

    Principal Research Systems Engineer (advanced L3)

    5-7 years in this role, with significant project leadership

    Skills to master

    • Deep technical expertise in a specific domain (e.g., HPC or Lab Informatics), project management, leading technical initiatives, informal team leadership.

    You're ready to move on when

    • Recognised as the 'go-to' expert for a critical piece of research infrastructure.
    • Successfully led 3-4 complex technical projects, often involving cross-functional teams.
    • Provided significant mentorship and technical guidance to junior and mid-level engineers.
    • Proactively identified strategic opportunities for infrastructure improvement and presented them to leadership.

15Where this role leads

The long view: This work can lead to VP roles overseeing R&D technology, or into a Chief Technology Officer position covering the whole company.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Global Research Infrastructure Director is actually changing.

Where it leads

Roles this leads to

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Data Science Foundations, worked against Global Research Infrastructure Director.

Data Science Foundations Level 7

Applied to your work in Global Research Infrastructure Director

1. To enable the learner to define the scope and landscape of Data Science and differentiate the roles of Data Scientists from other IT professionals. 2. To enable the learner to evaluate key topics within Data Science, including data administration, governance, and big data sources. 3. To enable the learner to describe the architecture and core elements of Apache Hadoop. 4. To enable the learner to analyse the advantages and disadvantages of utilising Artificial Intelligence techniques in a business context. 5. To enable the learner to critically analyse the impact of Big Data on digital transformation within organisations and its effects on users. 6. To enable the learner to review strategies for ensuring data compliance and explain the responsibilities and challenges faced by data specialists.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

See Your Progress Grow Illustration
Global Research Infrastructure Director
  • GxP Compliance & System Validation (CSV)
  • HPC Architecture & Optimization
  • FAIR Data Principles Implementation
  • Scientific Data Lifecycle Management
  • Capital Expenditure (CapEx) Planning & Justification
  • Cloud FinOps for Research
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Global Research Infrastructure Director is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Director, Global Research Infrastructure (L6)

    3-5 years in the Manager role

    This is the next logical step, moving from managing a domain to managing multiple domains and managers, with broader strategic and budgetary responsibility for the entire global research infrastructure.

    • Multi-Domain Infrastructure Strategy Developing a cohesive strategy for HPC, lab informatics, data, and cloud across the entire global footprint.
    • Large-Scale Vendor & Partner Ecosystem Management Managing relationships with multiple strategic vendors and external partners.
    • M&A Due Diligence & Integration Assessing and integrating infrastructure during mergers and acquisitions.
    • Advanced Cloud Economics & Governance Optimising cloud spend and governance at an enterprise scale.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, your days are packed. As a Global Research Infrastructure Director Manager, you're juggling team leadership, budget management, strategic planning, and keeping demanding scientists happy. The good news? AI isn't just for the researchers anymore; it's a powerful co-pilot for you too.

Imagine cutting down on the tedious, time-consuming parts of your job—like sifting through vendor proposals or drafting budget justifications—so you can focus on the big-picture strategy and developing your team. AI tools are here to help you do just that, giving you back precious hours every week.

Predictive Infrastructure Monitoring

Use AI/ML models (e.g., via Datadog, Splunk) to analyse telemetry from HPC clusters and storage systems. This helps predict component failures or performance bottlenecks before they impact critical research jobs, moving you from reactive firefighting to proactive management. Think of it as a crystal ball for your servers.

Cloud Cost Anomaly Detection

Deploy AI-powered FinOps tools to automatically detect anomalous cloud spending in real-time. This could be a misconfigured analysis pipeline consuming thousands of pounds per hour. You'll get instant alerts, preventing budget overruns before they become a nasty surprise. No more sifting through massive cloud bills manually.

Vendor & Tech Spec Synthesis

Use Large Language Models (LLMs) to rapidly ingest and summarise dense technical documentation, whitepapers, and vendor proposals for new technologies. Imagine asking, 'Compare the key features and limitations of Lustre vs. GPFS for our cryo-EM workflow' and getting a concise summary in minutes. This drastically accelerates technology evaluation and RFI/RFP processes.

Budget Justification & Policy Drafting

Leverage generative AI to create first drafts of complex documents, such as a capital budget request for a new storage platform or a new data governance policy. It helps translate highly technical needs into business-friendly language that Finance and R&D leadership can actually understand. It seriously reduces the 'blank page' problem for administrative and strategic writing.

Common questions

Common questions

How do you become a Global Research Infrastructure Director?

Common routes in include Lead Research Infrastructure Architect (3-5 years in this role), Senior Manager, Enterprise IT Infrastructure (from another department) (4-6 years in a similar management role) and Principal Research Systems Engineer (advanced L3) (5-7 years in this role, with significant project leadership). Times vary with prior experience.

Where can a Global Research Infrastructure Director progress to?

This role can lead on to Director, Global Research Infrastructure (3-5 years in the Manager role), depending on the skills you build.

What new skills matter most for a Global Research Infrastructure Director?

Increasingly, AI Strategy & Governance for Research and Quantum Computing Readiness. These are the skills our record of this role lists as growing.

Free tools

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17Where to go from here

Other roles at Level 6

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in research and development

Stay in the field you know and move sideways rather than up.
If you leave this industry

The skills involved, strategic infrastructure management, GxP compliance, cloud FinOps, and leading technical teams in a scientific setting, apply elsewhere too. They can carry over to other life sciences companies, biotech startups, or technology leadership roles in other regulated industries.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my free Automation Fluency module What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.