What You'll Do

Are you energized by building and scaling enterprise-grade AI platforms that power innovation across a complex organization?

As AI Infrastructure Director, you'll design, manage, and optimize the firm's AI infrastructure-spanning on-premise GPU environments and Microsoft Azure-based AI platforms-to enable enterprise AI, automation, and innovation initiatives at scale.

This role sits at the intersection of technology, governance, and business impact. You'll be the single point of accountability for AI-specific environments and shared AI platform services, partnering closely with Cloud Engineering, AI Engineering, and the Chief Growth Office (CGO) to ensure secure, reliable, and scalable delivery aligned with firm priorities. You'll also lead and grow a multi-disciplinary engineering organization responsible for the operational excellence of the firm's AI platforms.

• AI Infrastructure Ownership: Lead all AI environments-including on-premise Graphics Processing Unit (GPU) clusters, Microsoft Azure AI and Machine Learning (ML) services, and shared AI platform components-with accountability for reliability, scalability, and lifecycle management.
• Azure AI Environment Leadership: Own Azure environments hosting AI and automation workloads, including shared services such as Azure OpenAI, Azure AI Foundry, Azure AI Search, and Azure Kubernetes Service (AKS).
• Cross-Team Partnership: Collaborate with Cloud Engineering on landing zones, networking, subscription governance, and service onboarding, and with the AI Engineering Lead on shared platforms and operating standards.
• Innovation Enablement: Create secure, governed environments that enable rapid experimentation and development for Innovation, AI Engineering, and CGO teams.
• Team Leadership & Development: Lead AI Infrastructure, AI Platform Engineering, Azure AI Engineering Operations, and Microsoft 365 (M365) Automation functions; mentor leaders and engineers and build sustainable career paths.
• Platform Design & Delivery: Oversee the design and deployment of shared and custom AI platforms that accelerate solution delivery while meeting security and governance standards.
• Security & Responsible AI: Operationalize governance, privacy, and Responsible AI standards in partnership with Risk, Security, and Responsible AI teams.
• Operational Excellence: Ensure platform reliability, service-level objectives, incident response readiness, and continuous improvement across production AI environments.
• Strategic Planning & Vendor Management: Manage cloud operating budgets, vendor relationships, and capacity planning across Azure services, GPU infrastructure, and AI tooling.

What You'll Bring

• Education & Certifications: Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field required; Master's degree or Master of Business Administration (MBA) strongly preferred. Advanced Microsoft Azure certifications (e.g., Azure Solutions Architect Expert, DevOps Engineer Expert) strongly preferred.
• Leadership Experience: 12+ years in infrastructure, platform, or cloud engineering within complex enterprises, including at least 5 years in senior leadership roles managing managers and multi-team organizations.
• AI Platform Expertise: 5+ years designing, operating, and scaling production AI and ML platforms, including MLOps, Continuous Integration and Continuous Delivery (CI/CD), Infrastructure-as-Code, and containerized platforms such as Kubernetes and Docker.
• Azure at Scale: Deep expertise with enterprise-scale Microsoft Azure, including AI and ML services, networking, identity, security, governance, and cost management.
• Hybrid Infrastructure Knowledge: Experience integrating and operating on-premise GPU and high-performance computing environments with cloud platforms.
• Operational Accountability: Proven ownership of platform reliability, incident command, and service-level objectives in regulated, compliance-sensitive environments.
• Governance & Risk Awareness: Working knowledge of Responsible AI, AI risk management, regulatory frameworks, and compliance standards such as SOC 2 and ISO 27001.
• Financial & Vendor Acumen: Experience managing cloud spend using Financial Operations (FinOps) practices and overseeing enterprise vendor and contract relationships.
• Executive Communication: Strong executive presence with the ability to advise senior leaders and influence cross-functional stakeholders.
• Industry Context: Experience in legal, professional services, or similarly regulated environments preferred, including familiarity with legal technology ecosystems.

If you're excited to shape enterprise AI platforms, lead high-impact engineering teams, and enable responsible innovation at scale in this AI Infrastructure Director 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: $302,000 - $335,000

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.