Kirkland & Ellis LLP

AI Infrastructure Senior Engineer I

Kirkland & Ellis LLP$133K — $166K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field
  • Relevant Microsoft Azure certifications (e.g., Azure Administrator Associate)
  • 4-6 years in cloud infrastructure, platform engineering, or site reliability roles
  • At least 3 years of production experience with Microsoft Azure
  • Hands-on experience with Azure services, infrastructure-as-code, and Kubernetes (AKS)
  • Strong scripting skills in Python and PowerShell
  • Understanding of enterprise networking, access management, and secure cloud architecture

Responsibilities

  • Implement Infrastructure-as-Code (IaC) using tools like Terraform or Bicep
  • Configure and maintain networking, identity and access, and secret management aligned to security best practices
  • Monitor platform health and troubleshoot incidents using Azure Monitor and related tools
  • Manage capacity, scaling, and performance for AI services
  • Execute platform updates, maintenance, and upgrades following established change management processes
  • Enforce security controls and governance policies, addressing vulnerabilities as needed
  • Drive visibility into platform usage and optimize costs through proper resource management
  • Create and maintain clear documentation and contribute to platform enhancements

Benefits

  • Comprehensive healthcare coverage
  • Generous paid time off policy
  • Retirement savings plans
  • Personal support services
  • Tailored learning and development opportunities
Full Job Description
What You'll Do

Are you passionate about building and operating secure, scalable AI platforms that power real-world innovation?

As an AI Infrastructure Engineer, you'll play a key role in shaping and supporting a modern AI platform within the Information Technology team, specifically the AI Infrastructure group. You'll help ensure the reliability, performance, and scalability of shared AI services, enabling engineering and automation teams to deliver impactful solutions efficiently. Working closely with Cloud Engineering and other technology partners, you'll contribute to a high-performing, enterprise-grade environment supporting advanced AI capabilities across the firm.
Platform Build & Configuration: Implement Infrastructure-as-Code (IaC) using tools like Terraform or Bicep, maintain standardized Azure environments, and manage core services such as Azure OpenAI, Azure AI Foundry, Azure Kubernetes Service (AKS), and Azure AI Search.
Cloud Environment Management: Configure and maintain networking (private endpoints, hub-and-spoke architecture, network security groups), identity and access (Microsoft Entra ID, Managed Identity), and secrets (Azure Key Vault) aligned to security best practices.
Operational Monitoring & Reliability: Monitor platform health using Azure Monitor, Application Insights, and Log Analytics; respond to alerts, troubleshoot incidents, and support on-call rotations to maintain service continuity.
Capacity & Performance Optimization: Manage quotas, scaling, and performance for AI services while supporting capacity planning aligned to business growth.
Change & Release Enablement: Execute platform updates, maintenance, and upgrades using established change management processes while supporting onboarding of new AI workloads.
Security & Compliance: Enforce security controls, governance policies, and Responsible AI practices; remediate vulnerabilities and support audit and compliance reporting.
Cost Management & Optimization: Drive visibility into platform usage and costs, ensuring proper tagging, rightsizing, and efficient resource allocation.
Documentation & Continuous Improvement: Create and maintain clear documentation, runbooks, and operational procedures while contributing to platform enhancements and roadmap evolution.

What You'll Bring
Education & Certifications: Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, along with relevant Microsoft Azure certifications (e.g., Azure Administrator Associate or similar).
Experience: 4-6 years in cloud infrastructure, platform engineering, or site reliability roles, including at least 3 years working with Microsoft Azure in production environments.
Cloud & Platform Expertise: Hands-on experience managing Azure services, infrastructure-as-code, Kubernetes (AKS), and enterprise cloud environments with a focus on reliability and scalability.
Automation & Scripting: Strong scripting capabilities in Python and PowerShell to support automation, tooling, and operational efficiency.
Networking & Identity: Solid understanding of enterprise networking, access management, and secure cloud architecture.
Monitoring & DevOps Practices: Experience with observability tools, CI/CD pipelines, and modern deployment practices, including GitOps and policy-as-code.
AI Platform Exposure: Familiarity with Azure-based AI services and platform-level considerations such as capacity management, content controls, and governance.
Collaboration & Communication: Ability to work cross-functionally with engineering, infrastructure, and security teams while translating complex technical concepts into practical outcomes.
Operational Excellence Mindset: Experience in incident response, on-call support, and continuous improvement within production environments.

If you're excited to help build and operate cutting-edge AI infrastructure, collaborate with high-performing teams, and drive meaningful platform innovation in this AI Infrastructure Engineer role, we'd love to hear from you!

Compensation

The base salary range below represents the low and high end of the salary range for this position in Chicago. This range may differ based on your geographic location and cost of living considerations. At Kirkland & Ellis, we consider compensation more than just a base salary. We offer an exceptional range of flexible benefits including comprehensive healthcare, paid time off, and retirement. We also offer personal support and tailored learning and development opportunities all designed to help you realize your full potential both in life and at work.

Compensation Range:

Chicago: $133,000 - $166,000

How to Apply

Thank you for your interest in Kirkland & Ellis LLP. To complete an application and submit your resume, please click "Apply Now."

Don't meet every job requirement? That's okay! If you're excited about this role but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others at Kirkland.

About Kirkland & Ellis LLP

Kirkland & Ellis LLP is an American law firm. Founded in 1909 in Chicago, Illinois, Kirkland & Ellis is the largest law firm in the world by revenue, the seventh-largest by number of attorneys, and is the first law firm in the world to reach US$4 billion in revenue. As of 2021, Kirkland & Ellis ranks third on Am Law's list of profits per equity partner. While Kirkland & Ellis was historically considered a firm focused on litigation, during the 2010s, it expanded private equity and restructuring practices which, together with large-scale commercial litigation, comprise the core legal service areas of the firm. Many attorneys from the firm have served as federal officials or judges, including United States Supreme Court Justice Brett Kavanaugh and former Attorney General William Barr.
Learn more about Kirkland & Ellis LLP
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