Platform Engineer

Faculty

. Design, build, and deploy robust, secure, and scalable cloud infrastructure for AI and machine-learning workflows .

Posted 11/9/2026full-timeLondon • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying cloud infrastructure for AI and machine learning workflows, with a strong focus on Infrastructure as Code and containerization. Proven ability to collaborate with diverse stakeholders and implement best practices in cloud security and CI/CD processes.

Highest-signal resume keywords

Azure ExpertiseAWS ExpertiseInfrastructure As Code (Terraform)Containerization (Docker, Kubernetes)CI/CD and GitOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cloud Infrastructure DesignMachine Learning WorkflowsNetworking KnowledgeCloud SecurityRequirements GatheringTechnical PlanningScopingOpen-Source Technology IntegrationReusable Code RepositoriesOutcome-Focused Approach

Soft Skills

CollaborationPragmatic Problem-SolvingClient InteractionAdaptabilityLearning Agility

Tools & Technologies

TerraformDockerKubernetesCI/CD ToolsGitOps

Industry Keywords

Cloud InfrastructureAI WorkflowsMachine LearningInfrastructure As CodeContainerization

Tech Stack

Tools & technologies

AWSAzureCloudDockerKubernetesTerraform

About the role

Key responsibilities & impact

Design, build, and deploy robust, secure, and scalable cloud infrastructure for AI and machine-learning workflows
Partner with technical and non-technical stakeholders from initial idea generation through implementation and shipping
Enable Machine Learning Engineers and Data Scientists through internal best practices, standards, and reusable code repositories
Identify and recommend ways customers can leverage cloud infrastructure to solve key challenges
Create and maintain reusable company-wide libraries and infrastructure-as-code
Research and integrate open-source technologies to enhance Faculty’s infrastructure capabilities
Participate in talent screening, pair programming, system design, and commercial interviews

Requirements

What you’ll need

Deep experience with both Azure and AWS
Experience with Infrastructure as Code, especially Terraform
Experience building and deploying containerized solutions using Docker and Kubernetes
Strong CI/CD and GitOps practices
Proficient knowledge of networking and cloud security
Experience working directly with clients and stakeholders
Ability to handle requirements gathering, technical planning, and scoping
Pragmatic and outcome-focused approach
Scientific approach to testing assumptions and seeking evidence
Drive to learn and explore new technologies
Must answer whether UK visa sponsorship is required now or in the future

Benefits

Comp & perks

Hybrid working arrangement
Flexible part-time hours may be discussed
Opportunity to work on impactful AI solutions in life sciences, healthcare, and other sectors
Collaborative cross-functional work with technical and non-technical stakeholders
Diversity and inclusion-oriented workplace
Human-reviewed applications
Option to opt out of AI note-taking during interviews