UserTesting

2 days ago

IT Infrastructure Engineer – AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Job Summary

Build and maintain AI enablement infrastructure by deploying and operating MCP servers, AI agent environments, and hosting for internally built AI applications. Engineer reliable AWS/GCP infrastructure and DevOps toolsets, including CI/CD and infrastructure-as-code for secure deployments. Monitor uptime, performance, and cost with observability tools, troubleshoot complex integrations, and partner with security and engineering to improve governance and adoption.

Location: United Kingdom

Workplace: Remote

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Set up, configure, and maintain MCP servers that connect AI systems to internal tools and data sources, including access scoping, credential management, and troubleshooting integrations.
•Design, provision, and support hosting environments for internally built AI applications on AWS/GCP, including VPCs, compute, containers, and load balancing.
•Provision and support AI agent/application infrastructure, including service accounts, API key management, permissions scoping, rate limit monitoring, and access auditing.
•Build and maintain CI/CD pipelines and infrastructure-as-code for repeatable, secure deployments of AI-hosted applications and supporting services.
•Support cloud infrastructure administration and DevOps toolsets; monitor uptime, performance, and cost with observability tools and act as an escalation point for complex hosting/infrastructure issues.

Key Requirements

•5+ years of experience with cloud infrastructure and/or DevOps engineering, ideally with direct AWS and/or GCP experience (compute, networking/VPCs, IAM, storage).
•Practical experience deploying and hosting applications across AWS/GCP cloud infrastructure.
•Hands-on experience with AI concepts like MCP and AI agents.
•Strong scripting and automation skills in Python and/or Bash, plus comfort with JSON/YAML and Git for version control.
•Experience with containerization and orchestration (Docker/Podman; Kubernetes, ECS, or Cloud Run) and infrastructure-as-code/CI/CD (Terraform, CloudFormation, Pulumi; GitHub Actions).

Experience:5+ yearsCloud infrastructureDevOpsAI enablement

Skills:CommunicationStakeholder managementTroubleshootingProject leadership

Tech Stack:AWSGCPVPCsIAMTerraformCloudFormationPulumiGitHub ActionsDatadogCloudWatchMCP (Model Context Protocol)AI agentsPythonBashGitJSONYAMLDockerPodmanKubernetes

Company Brief

UserTesting

Provides a user experience research platform that enables companies to capture on-demand video feedback, usability testing, and customer insights to improve products, websites, and digital experiences across design, product, and marketing teams.

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 100M to 250M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2007

Glassdoor: 3.8

Website LinkedIn

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UserTesting

2 days ago

IT Infrastructure Engineer – AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 17 hours agoStatus: Live

Job Summary

Location: United Kingdom

Workplace: Remote

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Set up, configure, and maintain MCP servers that connect AI systems to internal tools and data sources, including access scoping, credential management, and troubleshooting integrations.
•Design, provision, and support hosting environments for internally built AI applications on AWS/GCP, including VPCs, compute, containers, and load balancing.
•Provision and support AI agent/application infrastructure, including service accounts, API key management, permissions scoping, rate limit monitoring, and access auditing.
•Build and maintain CI/CD pipelines and infrastructure-as-code for repeatable, secure deployments of AI-hosted applications and supporting services.
•Support cloud infrastructure administration and DevOps toolsets; monitor uptime, performance, and cost with observability tools and act as an escalation point for complex hosting/infrastructure issues.

Key Requirements

•5+ years of experience with cloud infrastructure and/or DevOps engineering, ideally with direct AWS and/or GCP experience (compute, networking/VPCs, IAM, storage).
•Practical experience deploying and hosting applications across AWS/GCP cloud infrastructure.
•Hands-on experience with AI concepts like MCP and AI agents.
•Strong scripting and automation skills in Python and/or Bash, plus comfort with JSON/YAML and Git for version control.
•Experience with containerization and orchestration (Docker/Podman; Kubernetes, ECS, or Cloud Run) and infrastructure-as-code/CI/CD (Terraform, CloudFormation, Pulumi; GitHub Actions).

Experience:5+ yearsCloud infrastructureDevOpsAI enablement

Skills:CommunicationStakeholder managementTroubleshootingProject leadership

Tech Stack:AWSGCPVPCsIAMTerraformCloudFormationPulumiGitHub ActionsDatadogCloudWatchMCP (Model Context Protocol)AI agentsPythonBashGitJSONYAMLDockerPodmanKubernetes

Company Brief

UserTesting

Industry: Enterprise Software

Company Size: Enterprise (1,001+ employees)

Revenue: USD 100M to 250M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2007

Glassdoor: 3.8

Website LinkedIn