Infrastructure Architect - Cloud, DevOps & AI/ML

Summary

Design and support secure, scalable cloud, on-premises, and hybrid infrastructure with emphasis on IaC, containers, networking, storage, and AI/ML workload infrastructure using AWS, Azure, or GCP.

  • On-premises infrastructure
  • Virtualisation
  • Scalable compute environments
  • Secure infrastructure design

We are looking for Infrastructure Architects and experienced Cloud Infrastructure professionals to design and support secure, resilient, scalable, high-performance, and cost-effective infrastructure across cloud, on-premises, and hybrid environments.

The role focuses on designing the infrastructure foundation for modern enterprise solutions, with particular emphasis on cloud platforms, compute, storage, networking, containerisation, Infrastructure-as-Code, high availability, disaster recovery, and data-intensive/AI/ML workloads.

Candidates with different levels of experience are encouraged to apply, from strong infrastructure/cloud engineers looking to move into architecture through to experienced Infrastructure Architects.

Key Responsibilities

  • Design end-to-end infrastructure architectures across cloud, on-premises, and hybrid environments
  • Define architecture across compute, storage, networking, databases, and platform services based on business and technical requirements
  • Design infrastructure requirements for data-intensive and AI/ML workloads, including GPU compute, high-throughput storage, scalable processing, and inference environments
  • Establish and maintain standards for Infrastructure-as-Code (IaC), environment management, automation, and configuration consistency
  • Design highly available infrastructure architectures with appropriate backup, disaster recovery, business continuity, RTO and RPO requirements
  • Ensure infrastructure designs meet security, compliance, data residency, and regulatory requirements
  • Perform capacity planning and cost optimisation, including resource right-sizing based on workload requirements
  • Review infrastructure architecture and technical changes and provide guidance to infrastructure, cloud, DevSecOps, and engineering teams
  • Support implementation teams by providing architecture guidance, technical standards, and recommended design patterns
  • Evaluate emerging cloud and infrastructure technologies and provide recommendations for adoption where appropriate
  • Contribute to infrastructure modernization, cloud migration, scalability, resilience, and performance improvement initiatives

Core Technical Skills

Cloud & Hybrid Infrastructure

Experience with one or more major cloud platforms:

  • AWS
  • Microsoft Azure
  • Google Cloud Platform (GCP)
  • Hybrid cloud environments
  • On-premises infrastructure

Candidates with strong expertise in one cloud platform are welcome, while multi-cloud experience will be an advantage.

Compute, Networking & Storage

Strong understanding of infrastructure architecture across:

  • Compute
  • Networking
  • Storage
  • Virtualisation
  • Load balancing
  • High availability
  • Disaster recovery
  • Backup and recovery
  • Business continuity
  • Performance and capacity planning

Containers & Platform Technologies

Experience with:

  • Docker
  • Kubernetes
  • Container orchestration
  • Container-based infrastructure
  • Cloud-native platform architectures

Infrastructure-as-Code & Automation

Experience with Infrastructure-as-Code and configuration management tools such as:

  • Terraform
  • AWS CloudFormation
  • Azure Bicep
  • Ansible
  • Other infrastructure automation tools

Strong understanding of environment management, configuration consistency, automation, and repeatable infrastructure deployment is required.

AI/ML & Data Infrastructure

Experience designing infrastructure for data-intensive and AI/ML workloads is highly desirable.

Relevant experience may include:

  • GPU compute infrastructure
  • High-throughput storage
  • Scalable compute environments
  • AI/ML infrastructure
  • Model training infrastructure
  • Model inference environments
  • Data processing workloads
  • Performance and capacity optimisation for AI/ML workloads

Security & Compliance

Strong understanding of:

  • Infrastructure security
  • Security architecture
  • Identity and Access Management (IAM)
  • Authentication and authorization
  • Network security
  • Cloud security
  • Data protection
  • Compliance requirements
  • Data residency
  • Secure infrastructure design

The successful candidate should be able to incorporate security and compliance requirements into infrastructure architecture rather than treating them as an afterthought.

High Availability & Disaster Recovery

Experience designing resilient infrastructure with consideration for:

  • High Availability (HA)
  • Disaster Recovery (DR)
  • Backup strategies
  • Business Continuity
  • RTO - Recovery Time Objective
  • RPO - Recovery Point Objective
  • Failure recovery
  • Resilience and redundancy

Architecture & Leadership Responsibilities

For senior-level candidates, responsibilities may include:

  • Reviewing and approving infrastructure designs
  • Establishing infrastructure architecture standards and reference patterns
  • Providing technical direction to infrastructure and DevSecOps engineers
  • Leading architecture discussions and design reviews
  • Conducting technology evaluations and making adoption recommendations
  • Mentoring engineers and supporting technical capability development
  • Driving infrastructure modernization and

See also

ML / AI jobs by country — openings, pay and top skills →

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