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UserTesting

On-demand usability testing and insights platform

IT Infrastructure Engineer - AI

Cloud EngineeringConfirmed live in the last 24 hours
Full-timeRemote in UKNo salary listed

About the Job

Requirements

  • Able to work Monday through Friday in UK or Spain (Barcelona) time zones.
  • Have 5+ years of experience with cloud infrastructure and/or DevOps engineering, ideally with direct AWS and/or GCP experience in compute, networking/VPCs, IAM, and storage.
  • Have practical experience deploying and hosting applications across AWS or GCP cloud infrastructure.
  • Have hands-on experience with AI concepts such as MCP, AI agents, and other AI-related technologies.
  • Have strong scripting and automation skills in Python and/or Bash, working knowledge of Git for version control, and comfort with JSON/YAML for configuration and API work.
  • Have experience with containerization using Docker or Podman and container orchestration such as Kubernetes, ECS, or Cloud Run, including running and troubleshooting containerized services.
  • Have experience with infrastructure-as-code tooling such as Terraform, CloudFormation, or Pulumi and CI/CD pipelines such as GitHub Actions.
  • Be familiar with API-based integrations, including managing keys, scoping permissions, reading documentation, and troubleshooting connectivity issues.
  • Be able to train and mentor IT staff on infrastructure and DevOps practices as they apply to the role and function.
  • Be familiar with identity provider tools such as Okta, and with OAuth and SSO from an infrastructure and security perspective.
  • Be able to learn in a constantly shifting environment.

Responsibilities

  • Set up, configure, and maintain MCP servers connecting AI systems to internal tools and data sources, including scoping access, managing credentials, and troubleshooting integrations.
  • Design, provision, and support hosting environments for internally built AI applications, ranging from lightweight PaaS deployments to full AWS/GCP cloud infrastructure—including VPCs, compute, containers, and load balancing—according to application complexity and scale requirements.
  • Provision and support AI agent and application infrastructure, including service accounts, API key management, permissions scoping, rate-limit monitoring, and access auditing for agents operating across internal systems and cloud environments.
  • Build and maintain CI/CD pipelines and infrastructure-as-code to support repeatable, secure deployment of AI-hosted applications and supporting services.
  • Maintain documentation for AI integrations and hosted environments, including architecture diagrams, access maps, runbooks, cost and usage tracking, and troubleshooting guides.
  • Stay current on the AI tooling and cloud ecosystem and identify tools, platforms, or integrations that could benefit the IT team or broader organization.
  • Support administration of the company's IT cloud infrastructure (AWS and/or GCP) and DevOps toolset across the organization as it relates to IT's AI infrastructure.
  • Become a subject matter expert for AI-hosted platforms, cloud integrations, and supporting infrastructure.
  • Monitor uptime, performance, and cost of hosted AI applications; implement alerting and observability to identify issues before they affect users.
  • Identify, prioritize, and address technical debt across cloud infrastructure, deployment pipelines, and integrations.
  • Partner with IT system administrators and Engineering/Security teams to improve reliability, automation, documentation, and supportability of hosted environments.
  • Act as an escalation point for complex infrastructure and hosting issues for the IT support team.
  • Collaborate with cross-functional teams, including Security, Engineering, and People Operations, to improve cloud governance, security posture, and adoption of AI tool and application hosting.
  • Manage stakeholders and act as a project lead at times, interacting, demonstrating, and collaborating with nontechnical counterparts.
  • Document procedures, system changes, and troubleshooting workflows.

Desired Qualifications

  • Familiarity with AI features within existing SaaS platforms such as Atlassian Rovo, Slack AI, Okta AI, ChatGPT, and Google Gemini.
  • Experience with MCP servers or similar tooling is a plus.
  • Certifications in cloud or AI platforms such as AWS, Google Cloud, or Anthropic are a plus; hands-on experience is valued more highly, and candidates should be prepared to explain it with real-world examples.

About the Company

UserTesting

On-demand usability testing and insights platform

UserTesting provides an on-demand experience research platform that helps teams collect feedback from real people on websites, apps, prototypes, and marketing content. Its SaaS product supports usability testing, interviews, and surveys, plus AI-assisted analysis, drawing on a large contributor network to deliver video recordings and written responses. The platform is used by thousands of subscription customers, including many Fortune 100 companies. Unlike some competitors, UserTesting combines a broad global pool of participants with multiple research methods and analytics in one integrated platform, enabling rapid, structured insights for product, design, research, and marketing teams. The company aims to turn customer feedback into actionable product and design decisions that improve user experiences and business outcomes.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2007

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