AI Infrastructure Senior Engineer I

About Kirkland & Ellis

At Kirkland & Ellis, we don’t just meet the standard for legal excellence — we set it. Our culture is built on teamwork, ingenuity and an unwavering commitment to continuous growth. We tackle the most sophisticated legal challenges with bold ideas and innovative solutions, powered by the exceptional experience and ambition of our 7,000+ people, including 4,000+ attorneys, across 24 offices worldwide. Our dedicated professionals share our lawyers’ commitment to excellence and show up each day to do meaningful work that helps drive global business, investment and innovation forward.

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.

Equal Employment Opportunity

All employment decisions, including the recruiting, hiring, placement, training availability, promotion, compensation, evaluation, disciplinary actions, and termination of employment (if necessary) are made without regard to the employee’s race, color, creed, religion, sex, pregnancy or childbirth, personal appearance, family responsibilities, sexual orientation or preference, gender identity, political affiliation, source of income, place of residence, national or ethnic origin, ancestry, age, marital status, military veteran status, unfavorable discharge from military service, physical or mental disability, or on any other basis prohibited by applicable law.