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AI Operations Engineer II

https://www.microsoft.com/ Logo

Microsoft Corporation

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Location:
United States , Multiple Locations

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

100600.00 - 199000.00 USD / Year
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Job Description:

The Security AI Platform team builds and operates production infrastructure that powers AI-native security capabilities at Microsoft scale. The AI Operations group is responsible for deployments, CI/CD pipelines, production reliability, and first-level on-call. We work closely with the Platform + Apps team who develops the core product features. We are seeking an AI Operations Engineer II to build and maintain operational infrastructure for the platform. In this role, you will work on CI/CD pipelines, Kubernetes deployments, monitoring systems, and incident response. You will develop expertise in production operations while contributing to reliability improvements with guidance from senior engineers.

Job Responsibility:

  • Maintain and extend CI/CD pipelines within established patterns: Azure DevOps/GitHub Actions workflows, build automation, test integration, and deployment scripts
  • Manage Kubernetes deployments: Helm chart updates, deployment execution, pod troubleshooting, and resource configuration
  • Develop and maintain observability: Prometheus metrics collection, Grafana dashboard creation, alerting rules, and log queries (Kusto/KQL)
  • Participate in on-call rotation: respond to alerts, triage incidents, escalate appropriately, and document findings
  • Debug and diagnose issues: analyze logs, traces, and metrics to identify problems
  • work with senior engineers on complex issues
  • Maintain Infrastructure as Code: update Bicep templates, Helm values, and environment configurations
  • Ensure branch health: monitor PR pipelines, address build failures, maintain security scanning, and enforce merge policies
  • Execute production deployments: run canary rollouts, monitor deployment health, and perform rollbacks when needed
  • Write and maintain runbooks: document operational procedures, troubleshooting guides, and deployment checklists
  • Collaborate with Platform team: understand service requirements, validate deployment readiness, and provide operational feedback
  • Participate in post-incident reviews: contribute to root cause analysis and implement reliability improvements

Requirements:

  • Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
  • Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
  • These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter

Nice to have:

  • Master's Degree in Computer Science or related technical field AND 3+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 5+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
  • 2+ years technical engineering experience in DevOps, SRE, or platform operations
  • 2+ years experience with CI/CD pipelines
  • 1+ years hands-on experience with Kubernetes
  • Experience with Azure services: AKS, Event Hub, Storage, Key Vault, or Managed Identity
  • Infrastructure as Code experience: Bicep, Terraform, or Helm chart development
  • Scripting proficiency: PowerShell, Bash, or Python for automation
  • Experience with log analysis and querying: KQL/Kusto, Loki, or ELK stack
  • Exposure to incident response and on-call responsibilities
  • Understanding of distributed systems concepts and troubleshooting approaches
  • Experience with container technologies: Docker, container registries, and image management
  • Familiarity with ML infrastructure: GPU nodes, inference servers, or model deployment

Additional Information:

Job Posted:
February 18, 2026

Employment Type:
Fulltime
Work Type:
Remote work
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