it infrastructure architect

<div>Role description 
Infrastructure Solution Architect (cloud architecture,azure iaas,windows server,euc administration)

Location: London (Hybrid, 3 days onsite) 
Employment Type: Permanent / Fixed-Term 


We are seeking a visionary Infrastructure Solution Architect to lead enterprise-wide technology architecture across a broad spectrum of infrastructure domains. This is a strategic leadership role, acting as a trusted advisor to senior stakeholders and shaping the future of complex infrastructure landscapes.

You will play a pivotal role in defining and delivering scalable, secure, and innovative solutions that enable business transformation, operational resilience, and long-term growth. 


Key Responsibilities
<ul>
<li>Define and lead the end-to-end infrastructure architecture strategy, ensuring alignment with digital transformation objectives</li>
<li>Design and govern scalable, high-performance, and secure solutions across multiple domains, including:
<ul><li>Wintel &amp; Linux platforms</li>
<li>Cloud (Azure, AWS, Hybrid environments)</li>
<li>Network (LAN, WAN, SD-WAN, Wireless, Firewalls)</li>
<li>Unified Communications (Cisco, Microsoft Teams)</li>
<li>Mobility &amp; Endpoint Management (Intune, UEM/MDM)</li>
<li>Observability &amp; Monitoring (e.g., ELK, Prometheus, AppDynamics)</li>
<li>End-User Computing (VDI, Citrix, M365, OS lifecycle)</li>
<li>Service Desk &amp; End-User Services (ITSM, automation, CSAT, FCR)</li>
</ul></li><li>Act as a trusted advisor to business and IT leaders, translating strategic objectives into future-ready technical solutions</li>
<li>Lead architecture governance, ensuring compliance with enterprise standards and regulatory frameworks</li>
<li>Drive infrastructure transformation initiatives, including cloud adoption, automation, Zero Trust, SASE, and containerization</li>
<li>Evaluate emerging technologies and provide strategic recommendations</li>
<li>Collaborate with engineering, security, DevOps, and delivery teams to ensure cohesive solution design</li>
<li>Develop reference architectures, blueprints, and roadmaps</li>
<li>Support RFP/RFI responses and pre-sales engagements for large-scale programs</li>
<li>Mentor and guide architects and senior engineers, fostering a culture of technical excellence and innovation</li></ul> 


What We're Looking For
<ul>
<li>Extensive experience in IT infrastructure and architecture, with broad exposure across multiple enterprise domains</li>
<li>Strong track record designing and delivering enterprise-scale infrastructure solutions</li>
<li>Deep expertise across cloud and on-premise environments (Azure, AWS, Hybrid)</li>
<li>Strong understanding of ITSM, ITIL, and service management frameworks</li>
<li>Knowledge of security frameworks, regulatory standards, and resilience planning (e.g., ISO, NIST, DR/BCP)</li>
<li>Exceptional stakeholder management, communication, and leadership skills</li></ul> 


Preferred Certifications
<ul>
<li>TOGAF or equivalent Enterprise Architecture certification</li>
<li>ITIL (v3 / v4)</li>
<li>Microsoft, Cisco, VMware, or Red Hat certifications</li>
<li>Cloud certifications (e.g., AWS Solutions Architect, Azure Solutions Architect)</li></ul> 


Hurry &amp; apply for a more detailed conversation!

#UST 
Skills 
cloud architecture,azure iaas,windows server,euc administration,azure ad,firewall,cloud security architecure,network design,citrix xenapp,netscaler,cisco aci,network security 
About UST 
UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world&rsquo;s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients&rsquo; organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact&mdash;touching billions of lives in the process.</div>

Infrastructure Solution Architect_London (Solution Architect II - Cloud Infrastructure Services)

Accenture

<div>YOU ARE
As a Lead and Principal Infrastructure Architect, you own end-to-end responsibility for designing optimized compute infrastructure for large-scale AI and machine learning systems, including large-scale distributed training environments. You are the authority who translates business goals, SLAs, and client standards into infrastructure architectures that perform at scale while being deliberately engineered for cost-efficiency.
Drawing on deep experience, you weigh multiple viable solutions for any given problem &mdash; across compute, networking, storage, orchestration, and model serving &mdash; and make rational, well-justified architectural decisions tailored to each client's situation, constraints, and standards. You architect and optimize the full computational stack for performance, power, cost, and scalability; design and tune large-scale GPU clusters and distributed training systems; and ensure infrastructure meets security, compliance, and regulatory requirements. As the recognized AI infrastructure expert in at least one hyperscaler cloud (such as AWS, Azure, or Google Cloud), you bring authoritative knowledge of that platform's AI/ML services, accelerators, networking, and cost levers, and apply it to deliver best-in-class solutions. Beyond design, you set technical direction and standards, lead and mentor engineers and architects, partner with clients and stakeholders to shape the infrastructure roadmap, and are ultimately accountable for delivering AI/ML infrastructure that meets business SLAs, controls cost, and scales to enterprise and frontier workloads.
THE WORK<ul><li>
Own the end-to-end architecture and design of optimized compute infrastructure for large-scale AI/ML systems, including large-scale distributed training environments, from concept through delivery.</li><li>
Develop and evaluate architecture alternatives, weighing trade-offs across compute, networking, storage, orchestration, and model serving to make rational, well-justified decisions tailored to each client's situation and standards.</li><li>
Lead architecture assessments and reviews of existing and proposed environments, identifying gaps, risks, bottlenecks, and optimization opportunities, and recommending remediation.</li><li>
Drive architectural decision-making, documenting rationale, trade-offs, and assumptions so decisions are transparent, defensible, and aligned with business SLAs and standards.</li><li>
Define and maintain the AI infrastructure roadmap, planning capacity, scaling, and technology evolution in step with business and product goals.</li><li>
Architect and optimize the full computational stack for performance, power, cost, and scalability, ensuring infrastructure meets business SLAs while being deliberately engineered for cost-efficiency.</li><li>
Design and tune large-scale GPU clusters and distributed training systems, including accelerator selection, interconnect/networking, and storage for high-throughput training workloads.</li><li>
Serve as the authoritative AI infrastructure expert in at least one hyperscaler cloud (AWS, Azure, or GCP), applying deep knowledge of its AI/ML services, accelerators, networking, and cost levers.</li><li>
Design deployment, automation, and CI/CD strategies for reliable, repeatable, and scalable releases of AI systems, models, and data pipelines into production.</li><li>
Establish AI monitoring and observability strategy across InfraOps and MLOps, defining SLAs, SLOs, alerting, and performance/cost tracking, and driving continuous optimization.</li><li>
Integrate AI/ML systems into enterprise environments, ensuring interoperability, security, compliance, and adherence to regulatory and client standards.</li><li>
Lead capacity planning and cost modeling, forecasting compute needs and engineering cost-efficiency into the architecture without compromising performance.</li><li>
Collaborate with clients, stakeholders, and engineering teams to align infrastructure decisions with business outcomes, translating requirements into actionable architecture and standards.</li><li>
Set technical direction, standards, and best practices, mentoring engineers and architects and leading design and code reviews across the team.</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Expertise in coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.</li><li>
Strong understanding of AI and machine learning as a subject.</li><li>
Strong understanding of computing infrastructure, preferred knowledge of AI infrastructure.</li><li>
Proficiency in programming languages such as Python, Java, or C++.</li><li>
Experience with data pipeline and workflow management tools (e.g., Apache Airflow, Kubeflow).</li><li>
Strong problem-solving skills and ability to work in a fast-paced environment.</li><li>
Excellent communication and collaboration skills.</li><li>
Experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large scale solutions.</li><li>
Proven experience in leading and managing AI projects and teams.</li><li>
Strong project management skills, with the ability to manage multiple projects simultaneously.</li><li>
Demonstrated experience in evaluating and selecting AI technologies and frameworks.</li><li>
Ability to work with cross-functional teams and drive project alignment.</li></ul></div>

AI Infrastructure Architecture Manager

<div>YOU ARE
As a hands-on Infrastructure Architect, you are an experienced engineer with several years in infrastructure engineering who now takes on more complex, higher-impact work designing and optimizing the AI and machine learning infrastructure that powers real-world applications. Working alongside senior architects and engineers &mdash; and increasingly leading your own workstreams &mdash; you apply proven skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you architect and optimize infrastructure components, write and review code and deployment scripts, design and tune cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and build and optimize data pipelines that feed AI and ML workflows. You optimize the computational stack for performance, cost, power, and scalability, monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and independently troubleshoot and resolve complex issues across the stack. You also mentor junior engineers, contribute to architectural decisions, and help establish best practices. This is a hands-on, ownership-driven where you apply and deepen your expertise across modern tools and platforms &mdash; including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring &mdash; while making meaningful contributions to infrastructure that enables AI-driven business outcomes.
THE WORK<ul><li>
Write, review, and debug code, scripts, and infrastructure-as-code for AI infrastructure, automation, and tooling, setting standards for quality across the team.</li><li>
Architect, configure, and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups, optimizing for performance and utilization.</li><li>
Design and maintain deployment automation and CI/CD pipelines to support reliable, repeatable releases of AI systems, models, and applications.</li><li>
Deploy AI systems, models, and data pipelines into production, defining and improving the processes and best practices others follow.</li><li>
Lead container orchestration and model serving using tools such as Docker, Kubernetes, and model deployment frameworks.</li><li>
Architect and optimize the computational stack for performance, power, cost, and scalability, balancing trade-offs against business goals.</li><li>
Evaluate and select tools, frameworks, and platforms, making recommendations that shape the infrastructure roadmap.</li><li>
Integrate AI models and systems into existing enterprise systems, ensuring interoperability, security, and regulatory compliance.</li><li>
Own AI monitoring and infrastructure health across InfraOps and MLOps, tracking performance, reliability, and utilization, and driving remediation.</li><li>
Independently troubleshoot and resolve complex issues across the computational stack &mdash; hardware, networking, software, and models &mdash; and lead root-cause analysis.</li><li>
Mentor junior engineers and lead code reviews, providing technical direction and supporting their growth.</li><li>
Define and document architecture standards, processes, and procedures, and apply security, cost-efficiency, and scalability best practices across the infrastructure.</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experienced with coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.</li><li>
Strong understanding of AI and machine learning as a subject.</li><li>
Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure.</li><li>
Proficient in programming languages such as Python, Java, or C++.</li><li>
Experience with data pipeline and workflow management tools (e.g., Apache Airflow, Kubeflow).</li><li>
Strong problem-solving skills and ability to work in a fast-paced environment.</li><li>
Excellent communication and collaboration skills.</li><li>
Experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large scale solutions.</li></ul></div>

AI Infrastructure Architecture Specialist

<div>YOU ARE
As a hands-on Infrastructure architect, you are an early-career engineer who learns and grows while contributing hands-on to the AI and machine learning infrastructure that powers real-world applications. Under the guidance of senior architects and engineers, you'll develop practical skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you'll write and test code and deployment scripts, help configure cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and support data pipelines that feed AI and ML workflows. You'll learn to monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and troubleshoot issues across the computational stack with mentorship and support. This is a hands-on, learning-focused where you build expertise across modern tools and platforms &mdash; including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring &mdash; while making meaningful contributions to infrastructure that enables AI-driven busin
ess outcomes.
THE WORK<ul><li>
Write, test, and debug code and scripts for AI infrastructure tasks, including automation and tooling, under the guidance of senior engineers.</li><li>
Develop and maintain infrastructure and software deployment scripts to support reliable, repeatable releases of AI systems and models.</li><li>
Configure and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups.</li><li>
Deploy AI systems and machine learning models into production infrastructure, following established processes and best practices.</li><li>
Deploy data pipelines that feed AI and ML workflows, ensuring data is available, clean, and reliable.</li><li>
Assist with container orchestration and model serving, learning tools such as Docker, Kubernetes, and model deployment frameworks.</li><li>
Support and maintain CI/CD pipelines for automating the build, test, and deployment of AI infrastructure and applications.</li><li>
Monitor AI systems and infrastructure health across InfraOps and MLOps disciplines, tracking performance, reliability, and resource utilization.</li><li>
Perform AI monitoring to track model performance, detect drift or degradation, and surface issues for review.</li><li>
Troubleshoot and help resolve issues across the computational stack &mdash; hardware, networking, software, and models &mdash; with mentorship and support.</li><li>
Document configurations, processes, and procedures to maintain clear, repeatable, and shareable knowledge across the team.</li><li>
Collaborate with senior architects and engineers, participating in code reviews, team discussions, and knowledge-sharing sessions to grow technical skills.</li><li>
Apply security, cost-efficiency, and scalability best practices as you learn them, contributing to well-managed and responsible infrastructure.</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Work or coursework experience with AI/ML or Computer engineering or Computer science.</li><li>
Coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.</li><li>
Strong understanding of AI and machine learning as a subject.</li><li>
Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure.</li><li>
Proficiency in programming languages such as Python, Java, or C++.</li></ul></div>

AI Infrastructure Architecture Analyst

Securitas

<div>AWS Infrastructure Engineer
Location: United Kingdom
Purpose
Design, build, and operate AWS infrastructure that underpins key platforms and services as the organisation continues its transition to cloud.
Work as a hands-on AWS engineer, focused on delivering secure, scalable, and highly available environments. Take ownership of components of the migration and operation of business-critical platforms and services within AWS.
Major Responsibilities<ul><li>
Design, build, and maintain AWS infrastructure using infrastructure-as-code principles</li><li>
Support production and non-production environments with a focus on availability, performance, and security</li><li>
Deliver backend infrastructure operations including server management, updates, storage, failover, and logging</li><li>
Build and maintain core AWS services across compute, networking, storage, and identity (e.g. EC2, S3, VPC, IAM, RDS, CloudWatch)</li><li>
Collaborate with application, DevOps, and security teams to deliver resilient cloud solutions</li><li>
Integrate infrastructure with CI/CD pipelines to enable reliable, repeatable deployments</li><li>
Implement monitoring, logging, alerting, and observability practices</li><li>
Investigate incidents, contribute to root cause analysis, and drive continuous improvement</li><li>
Support security, compliance, and audit requirements within cloud environments, including regulated or security-sensitive contexts</li><li>
Work with cloud partners and vendors, including AWS and third parties, on architecture reviews and optimisation</li><li>
Automate infrastructure provisioning and operational processes to reduce manual effort</li><li>
Document infrastructure, standards, and operational processes</li><li>
Primary working hours aligned to European time zones. Participation in a global on-call rotation.</li></ul>
What Success Looks Like<ul><li>
Deliver stable, secure, and scalable AWS environments that support business-critical platforms</li><li>
Contribute to the successful migration and operation of core business platforms and services in AWS</li><li>
Maintain strong system availability and performance across production environments</li><li>
Identify and resolve infrastructure issues proactively, improving reliability over time</li><li>
Collaborate effectively with cross-functional teams to deliver consistent, high-quality solutions</li><li>
Establish reliable and repeatable infrastructure practices</li></ul>
Education<ul><li>
Degree or equivalent experience in Computer Science, Information Technology, or a related field</li></ul>
Experience &amp; Knowledge<ul><li>
Hands-on experience with AWS in production environments</li><li>
Strong knowledge of core AWS services such as VPC, IAM, EC2, containers, storage, and monitoring</li><li>
Experience with infrastructure-as-code tools (e.g. Terraform, AWS CDK, or similar)</li><li>
Understanding of cloud networking, security, and identity management</li><li>
Experience supporting highly available, business-critical systems</li><li>
Familiarity with cloud migration initiatives</li><li>
Experience integrating infrastructure with CI/CD pipelines and automation tooling</li><li>
Exposure to containerised workloads or orchestration platforms (e.g. ECS, EKS)</li><li>
Experience working within regulated or security-focused environments</li><li>
Experience working with distributed teams</li><li>
AWS certifications (e.g. Solutions Architect, SysOps Administrator) are beneficial</li></ul>
Skills &amp; Competencies<ul><li>
Strong problem-solving and troubleshooting skills</li><li>
Clear communication across technical and non-technical teams</li><li>
Collaborative approach to working with engineering, security, and operations</li><li>
Ability to prioritise and manage workload effectively</li><li>
Adaptability in a changing environment</li><li>
Commitment to continuous learning and improvement</li></ul>
Why Join Us
Work on meaningful cloud transformation initiatives, helping to move critical platforms into AWS. Contribute to real-world infrastructure challenges while collaborating with experienced teams across the organisation.
Develop AWS expertise, expand technical capability, and operate in an environment that values collaboration, learning, and practical problem solving.
Our People Promise &ndash; Securitas Technology EVP
Alongside the opportunity to work on modern AWS infrastructure, you&rsquo;ll be part of an organisation that values people, growth, and purpose. We offer clear career pathways, growth opportunities, recognition for achievements, and a global, collaborative team.
As part of our EVP, we offer:<ul><li>
Career pathways and growth opportunities</li><li>
A global, values-driven team</li><li>
Recognition for achievements</li><li>
An inclusive, collaborative culture</li><li>
Purposeful work that makes the world safer</li><li>
Support for innovation and sustainability</li></ul>
Securitas Technology is committed to diversity and is an equal opportunity employer; all qualified applicants are welcome.</div>

AWS Infrastructure Engineer

Google

<div><h3 class="jobSectionHeader">Minimum qualifications:</h3><ul>
<li>Bachelor's degree in Computer Science or equivalent practical experience.</li>
<li>3 years of experience building machine learning solutions and working with technical customers.</li>
<li>Experience designing cloud enterprise solutions and supporting customer projects to completion.</li>
<li>Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including data structures, algorithms, and software design.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>Experience working with recommendation engines, data pipelines, or distributed machine learning.</li>
<li>Experience with deep learning frameworks (e.g., TensorFlow, XGBoost).</li>
<li>Understanding of the auxiliary practical concerns in production machine learning systems.</li>
<li>Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce).</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google&rsquo;s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. 

As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. You will work closely with product management and product engineering to build and constantly drive excellence in our products. 
 
In this role, you are the Google engineer working with Google's largest and most motivated Cloud customers. Together with the team you will support customer implementation of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more. 
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Be a trusted technical advisor to customers and solve complex machine learning challenges.</li>
<li>Coach customers on the practical challenges in machine learning systems feature extraction and feature definition, data validation, monitoring, and management of features and models.</li>
<li>Work with customers, partners, and Google Product teams to deliver tailored solutions into production.</li>
<li>Create and deliver best practice recommendations, tutorials, blog articles, and sample code.</li>
<li>Travel up to 30% for in-region for meetings, technical reviews, and onsite delivery activities.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

AI Infrastructure Engineer

metropolitan gaming

<div>About Us
Metropolitan Gaming is about more than the games or the buzz of the venue. 
It&rsquo;s about energy. Atmosphere. Service that&rsquo;s sharp and in sync with the moment.
Driven by people, we&rsquo;re a diverse, close-knit team who back each other, celebrate wins and create great experiences together. If you&rsquo;re upbeat, curious and ready to get involved, you&rsquo;ll feel at home here. Personality matters. Every shift is a chance to make your mark.
 Why Join Us
A place to grow, not just a job. You&rsquo;ll be recognised for great work and given opportunities to build your skills and grow your career
Alongside competitive pay, you can also:
<ul><li>Discounts and perks across travel, retail, hospitality and wellbeing</li>
<li>Company pension scheme and life insurance cover</li>
<li>Discount on Food and non-alcoholic beverages across all venues</li>
<li>Season ticket loan and cycle to work scheme</li>
<li>Refer a friend bonus reward</li>
</ul>
What We Are Looking For:
The Senior Infrastructure Engineer is responsible for designing, implementing, supporting, and continuously improving the organization's IT infrastructure, cloud platforms, network services, and technical architecture. This role combines deep technical expertise with strategic thinking to ensure infrastructure remains secure, scalable, resilient, and aligned with business objectives.
Main Responsibilities
<ul><li>Provide strategic and operational leadership for the Infrastructure Engineering function, ensuring the design, implementation, support, and continuous improvement of enterprise infrastructure services.</li>
<li>Define and maintain infrastructure standards, architectures, and roadmaps aligned to business objectives and technology strategy.</li>
<li>Review and approve technical designs, change requests, and implementation plans proposed by MSP partners.</li>
<li>Act as the primary technical liaison between internal IT teams and external MSP partners.</li>
<li>Oversee the lifecycle management of servers, storage, virtualisation platforms, operating systems, and data centre technologies.</li>
<li>Manage third-party suppliers and technology vendors alongside MSP relationships.</li>
<li>Ensure infrastructure services meet agreed availability, performance, scalability, and resilience requirements.</li>
<li>Lead capacity planning, technology refresh programmes, and infrastructure modernisation initiatives.</li>
<li>Establish infrastructure governance processes, operational procedures, and technical standards to support secure and reliable service delivery.</li>
</ul><ul><li>Provide technical leadership and governance for technology programmes and projects, ensuring successful delivery of strategic initiatives.</li>
<li>Manage infrastructure-related budgets, forecasting, procurement activities, and vendor relationships to ensure cost-effective technology investments.</li>
</ul>
Who You Are
<ul><li>Bachelor's degree or equivalent experience; 7+ years infrastructure engineering experience; 3+ years cloud engineering experience; experience designing secure enterprise infrastructure solutions.</li>
<li>Experience working in an enterprise environment that utilises outsourced or co-managed MSP services.</li>
<li>Proven experience managing technical relationships with MSPs and third-party service providers.</li>
<li>Experience reviewing and challenging technical solutions proposed by external providers.</li>
<li>Good communication with the ability to build rapport and credibility at all levels</li>
<li>Collaborative, proactive, and customer-focused approach within a fast-paced environment</li>
<li>Excellent organisational, problem-solving, analytical, and critical thinking skills with the ability to prioritise and meet deadlines</li>
<li>Strong technical leadership and decision-making capability.</li>
<li>Ability to challenge suppliers constructively and hold them accountable.</li>
<li>Commercial awareness and vendor management skills.</li>
<li>Excellent communication and stakeholder engagement abilities.</li>
<li>Strategic thinker with a hands-on approach to infrastructure engineering.</li>
</ul>
Desirable Skills
<ul><li>Experience transitioning services between in-house teams and MSP providers.</li>
<li>ITIL Service Management practices.</li>
<li>Vendor and contract management.</li>
<li>Cybersecurity frameworks and operational resilience initiatives.</li>
</ul>
Technical Skills
Windows Server, Linux, VMware, Hyper-V, Active Directory, Microsoft 365, Azure, Cisco Meraki, Fortinet
Prefered Certifications
Azure Solutions Architect Expert, Azure Administrator Associate, Cisco CCNP</div>

Senior Infrastructure Engineer

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