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AI Engineer II

Kirkland & Ellis

📍 Chicago, Illinois, US0💼 Full-time🕐 6/3/2026
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Role overview

Kirkland & Ellis is hiring for the AI Engineer II role in Chicago, Illinois, US. It is full-time, Senior level, in the Tech sector. It was posted 6/3/2026.

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Role
AI Engineer II
Company
Kirkland & Ellis
Location
Chicago, Illinois, US
Work mode
On-site
Employment
Full-time
Seniority
Senior
Sector
Tech
Posted
6/3/2026

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 23 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 scalable, real-world AI solutions that transform how professionals work? As an AI Engineer II, you’ll design, build, and optimize enterprise AI solutions that power innovation across Information Technology’s Innovation Technology and Litigation Practice Technology (LPT) teams. Reporting to the AI Engineering Lead, you’ll take ownership of the full AI solution lifecycle—from architecture and deployment to evaluation and continuous improvement—while collaborating closely with cross-functional stakeholders. In this role, you’ll combine technical depth with practical impact, helping deliver secure, production-ready solutions while also mentoring junior engineers and contributing to the evolution of AI capabilities across the organization. Solution Architecture: Design scalable, secure AI architecture and translate business needs into actionable technical solutions and implementation plans. AI Development & Deployment: Build and deploy AI models, large language model (LLM)-powered applications, and retrieval-augmented generation (RAG) pipelines across enterprise environments. Quality & Evaluation: Create and manage evaluation frameworks including regression testing, benchmark datasets, and human-in-the-loop validation to ensure high-quality outputs. Troubleshooting & Optimization: Diagnose and resolve complex issues across AI systems and integrations, performing root cause analysis and implementing long-term fixes. Automation & Efficiency: Develop and enhance automated pipelines for AI delivery using tools like Azure DevOps, GitHub Actions, Python, and PowerShell. Security & Responsible AI: Ensure solutions meet security standards, data governance requirements, and Responsible AI (RAI) guidelines while complying with regulatory expectations. Collaboration & Mentorship: Partner with engineers, architects, and stakeholders across teams while mentoring junior team members and contributing to knowledge sharing. What You’ll Bring Education: Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; advanced degree or certifications (e.g., Microsoft Certified: Azure AI Engineer Associate) are a plus. Experience: 3–5 years of hands-on experience in software engineering, cloud engineering, or AI/machine learning (AI/ML) development with a track record of delivering solutions end-to-end. Programming & AI Development: Strong Python skills with experience building AI/ML models, APIs, and LLM or RAG-based solutions. Cloud & Platform Expertise: Experience with Microsoft Azure AI services (e.g., Azure Machine Learning, Azure OpenAI Service, Azure AI Search) along with Docker and Kubernetes (AKS). Engineering Practices: Familiarity with continuous integration and continuous delivery (CI/CD) pipelines, infrastructure as code (IaC) tools (Terraform or Bicep), and modern API/integration patterns. Evaluation & Optimization: Understanding of AI evaluation techniques, including prompt testing, benchmarking, and performance tuning. Technical Versatility: Experience with GPU environments, Linux systems, and frameworks such as LangChain, Semantic Kernel, or Azure Prompt Flow. Collaboration & Mindset: Strong problem-solving skills, a collaborative approach, and a passion for mentoring and continuous improvement. If you’re excited to build impactful AI solutions, collaborate with forward-thinking teams, and drive innovation in this AI Engineer II 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: $116,000 - $144,000 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.

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