AI Engineer II

Kirkland and Ellis
Houston, TX, United States
3 months ago
Apply on indeed.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$116,000.0 - $144,000.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Microsoft Azure Cloud Computing Cloud Engineering Computer Programming Data Governance Linux Github Python (Programming Language) Machine Learning Performance Tuning
+16 more
Windows PowerShell Regression Testing Azure Machine Learning Search Technologies Software Engineering Systems Integration Delivery Pipeline Large Language Models IT Architecture Build Management AI Platforms Infrastructure Automation Frameworks Information Technology Bicep Terraform Docker

Job description

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.

Requirements

Do you have experience in Python?, * 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!

Benefits & conditions

Pulled from the full job description

  • Health insurance
  • Paid time off, 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

About the company

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on indeed.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:14 min

Exploring internal AI product initiatives and global engineering roles

Maria Apazoglou · Coffee With Developers

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · World Congress 2025

52 sec

Running persistent Linux environments directly on Windows

Ben Breard Ben Breard · World Congress 2025

2:56 min

Provisioning a secure container infrastructure with Bicep

Matthias Falkenberg +1 · World Congress 2022

2:34 min

Docker sandbox architecture and microVM environment integration

Manuel de la Peña Manuel de la Peña · World Congress 2026 Europe

3:55 min

Demonstrating .NET installation on Debian and Azure Linux

Silvano Coriani Silvano Coriani · Europe 2026 Virtual

Videos

See all

Related articles

See all