About this role
The AI Engineer II designs, builds, deploys and improves secure, production-ready enterprise AI solutions for Kirkland & Ellis’s Innovation Technology and Litigation Practice Technology teams. Reporting to the AI Engineering Lead, the engineer owns the solution lifecycle and works with cross-functional stakeholders to address professional and litigation-technology needs.
Responsibilities
- Design scalable, secure AI architectures and turn business requirements into technical plans. Develop AI models, large language model (LLM) applications and retrieval-augmented generation (RAG) pipelines for enterprise use.
- Establish evaluation frameworks using regression tests, benchmark datasets and human-in-the-loop validation. Troubleshoot AI systems and integrations, identify root causes and implement lasting fixes.
- Automate AI delivery with tools such as Azure DevOps, GitHub Actions, Python and PowerShell. Meet security, data-governance, Responsible AI and regulatory requirements. Collaborate with engineers, architects and stakeholders, mentor junior engineers and share knowledge.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, Data Science or a related field, and 3–5 years of hands-on software engineering, cloud engineering or AI/ML development experience delivering solutions end to end.
- Strong Python skills and experience building AI/ML models, APIs and LLM- or RAG-based solutions. Experience with Azure Machine Learning, Azure OpenAI Service, Azure AI Search, Docker and Kubernetes (AKS); familiarity with CI/CD, infrastructure as code using Terraform or Bicep, and modern API and integration patterns.
- Understanding of prompt testing, benchmarking and performance tuning; experience with GPU environments, Linux and frameworks such as LangChain, Semantic Kernel or Azure Prompt Flow. Strong problem-solving, collaboration and mentoring skills. An advanced degree or relevant certification, such as Microsoft Certified: Azure AI Engineer Associate, is a plus.
The position is listed in Chicago with a hybrid-work tag. The Chicago base salary range is $116,000–$144,000 and may vary by geographic location and cost of living. Benefits mentioned include healthcare, paid time off, retirement, personal support, and learning and development opportunities.
Skills for this role
AI solution architecturePythonAI/ML model developmentLarge language modelsRetrieval-augmented generationAPI developmentAzure Machine LearningAzure OpenAI ServiceAzure AI SearchDockerKubernetesAzure Kubernetes ServiceCI/CDInfrastructure as codeTerraformBicepAI evaluationRegression testingBenchmarkingPrompt testingHuman-in-the-loop validationPerformance tuningAzure DevOpsGitHub ActionsPowerShellData governanceResponsible AIGPU environmentsLinuxLangChain Microsoft Semantic Kernel Azure Prompt Flow