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Ai Infrastructure Jobs in Elgin, IL (NOW HIRING)

Accenture

AI Infrastructure Operations Engineer

Chicago, IL · Hybrid

$110K - $145K/yr

The Global AI Infrastructure team enables resilient, high-performance compute environments for strategic clients across cloud, on-premises, and hybrid deployments. We design, build, and operate large ...

YO AI Labs

AI/ML Engineer - Remote

Chicago, IL · Remote

$200 - $350/hr

Remote Job Summary We are seeking an experienced AI/ML Engineer to build and deploy secure, scalable AI solutions for mission-critical initiatives while contributing to proprietary AI infrastructure.

Deloitte

HPC AI Solution Architect (S2S)

Chicago, IL

Lead Cloud HPC- AI Infrastructure Architect(S2S) As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team in Deloitte's AI & Engineering practice, you will design and drive deployment of ...

Optalysys

VP of Product

Mundelein, IL · On-site

VP Product Optalysys is building at the intersection of AI infrastructure, photonics, networking and advanced compute. At the heart of our technology is compute-in-transit: embedding programmable ...

YO AI Labs

Infrastructure Expert - Remote

Chicago, IL · Remote

$30 - $80/hr

Developer & Infrastructure Expert Role Type: Contractor Location: Remote Job Overview We are ... You will test AI-generated commands, configurations, and workflows and provide practical feedback ...

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All JobsAi Infrastructure JobsAi Infrastructure Jobs in Elgin, IL

Ai Infrastructure information

See Elgin, IL salary details

$27

$58

$86

How much do ai infrastructure jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for ai infrastructure in Elgin, IL is $58.50, according to ZipRecruiter salary data. Most workers in this role earn between $47.55 and $68.22 per hour, depending on experience, location, and employer.

What is AI infrastructure?

AI infrastructure refers to the combination of hardware, software, and cloud-based solutions that support the development, deployment, and scaling of artificial intelligence applications. It includes components such as GPUs, CPUs, storage systems, networking, data management tools, and machine learning frameworks. The goal of AI infrastructure is to provide the computational power and resources needed to train, test, and run AI models efficiently, whether on-premises or in the cloud. Organizations invest in robust AI infrastructure to accelerate innovation, manage large datasets, and ensure the reliability of their AI systems.

What are the key skills and qualifications needed to thrive in AI infrastructure?

To thrive in AI Infrastructure, you need expertise in software engineering, distributed systems, cloud platforms, and a solid understanding of machine learning workflows, often supported by degrees in computer science or related fields. Familiarity with tools like Kubernetes, Docker, Terraform, and cloud services (AWS, GCP, Azure), as well as experience with CI/CD pipelines and monitoring systems, is essential. Strong problem-solving abilities, effective communication, and adaptability help professionals excel in cross-functional teams and rapidly evolving environments. These skills and qualities are crucial for building scalable, reliable systems that power AI applications and support organizational innovation.

What are common challenges faced by professionals working in AI infrastructure roles, and how can they be addressed?

Professionals in AI Infrastructure roles often encounter challenges related to scalability, system reliability, and integration with existing IT environments. Managing rapidly growing datasets and ensuring seamless deployment of machine learning models can be complex, requiring robust automation and monitoring tools. Collaboration with data scientists, software engineers, and DevOps teams is critical to ensure infrastructure meets the evolving needs of AI projects. Staying updated with the latest cloud technologies and best practices can help address these challenges and drive successful AI implementations.

What is the difference between Ai Infrastructure vs Data Engineer?

AspectAi InfrastructureData Engineer
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of cloud platforms and AI toolsBachelor's in CS, Data Science, or related; programming and database skills
Work EnvironmentCloud environments, AI model deployment, infrastructure setupData pipelines, database management, data processing
Employer & Industry UsageTech companies, AI startups, cloud providersTech firms, finance, healthcare, e-commerce

Ai Infrastructure professionals focus on building and maintaining the hardware and software systems that support AI models, while Data Engineers develop and manage data pipelines and databases. Both roles require technical skills and often collaborate but serve different core functions within AI and data ecosystems.

What are AI infrastructure jobs?

AI infrastructure jobs involve designing, building, and maintaining the hardware, software, and network systems necessary to support artificial intelligence applications. These roles often require knowledge of cloud computing, data centers, machine learning frameworks, and system optimization to ensure reliable and efficient AI model deployment and operation.

What are popular job titles related to Ai Infrastructure jobs in Elgin, IL?

For Ai Infrastructure jobs in Elgin, IL, the most frequently searched job titles are:

What cities near Elgin, IL are hiring for Ai Infrastructure jobs?

Cities near Elgin, IL with the most Ai Infrastructure job openings:

Ai Infrastructure jobs near you
Infographic showing various Ai Infrastructure job openings in Elgin, IL as of August 2026, with employment types broken down into 75% Full Time, 23% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $121,689 per year, or $58.5 per hour.

AI Infrastructure Director

Kirkland & Ellis LLP

Chicago, IL • On-site

Other

Medical, Retirement, PTO

Re-posted 13 days ago

Kirkland & Ellis rating

8.3

Company rating: 8.3 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

18th of 35 rated law firms

Job description

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 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.
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. #LI-Hybrid #LI-LC1

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