Innovation AI Developer

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

Do you want to build artificial intelligence solutions that transform how a leading law firm serves clients and operates its business?

As an Innovation AI Developer within Innovation Engineering, you will create secure, scalable products that improve the quality, speed, and effectiveness of legal work and firm operations. Working closely with attorneys, innovation leaders, engineers, and data scientists, you will turn complex challenges into practical solutions using large language models (LLMs), classical machine learning (ML), and advanced analytics.

Reporting to the Director of Innovation Engineering, you will help build the firm’s Innovation Engineering program and lead solutions through the full development lifecycle, from experimentation and evaluation to deployment and monitoring. This firm-wide role has standard hours of 9:00 a.m. to 5:00 p.m., which may vary, and requires occasional travel.

• Partner with legal, business, and technical stakeholders to identify valuable use cases, turn complex needs into clear requirements, and define measurable outcomes related to efficiency, quality, and risk mitigation.
• Design and implement internal tools and workflows using artificial intelligence (AI) models, vector databases, orchestration frameworks, and modern user-interface platforms.
• Create retrieval-augmented generation (RAG) pipelines, AI agents, and applications supporting areas such as contract analysis, diligence review, document summarization, and legal research.
• Architect resilient AI solutions on Microsoft Azure and collaborate with infrastructure and security teams on cloud, local, and hybrid deployments involving sensitive legal and business data.
• Design and maintain evaluation frameworks that measure model accuracy, robustness, safety, business value, and alignment with specific use cases.
• Build internal libraries, documentation, and repeatable solution patterns that enable efficient, consistent development across the firm.
• Advise on prompt design, model selection, and evaluation methods while supporting pilots, demonstrations, user training, and feedback collection.
• Evaluate emerging tools, open-source libraries, vendor platforms, and third-party applications while contributing to technical diligence and technology decisions.
• Stay current on AI developments and contribute to presentations, internal training, thought leadership, and knowledge sharing for attorneys, business teams, colleagues, and clients.
• Work across Innovation, engineering, data science, legal, and business teams while supporting other engineers and helping coordinate technical workstreams.

What You’ll Bring

• A bachelor’s degree is required, preferably in computer science or a related field.
• At least four years of experience in professional services, legal, or technical roles, with demonstrated success in collaborative, team-based environments. Experience in a law firm is preferred.
• Strong Python development skills, proficiency with Structured Query Language (SQL), and the ability to work with databases, application programming interfaces (APIs), document repositories, and other structured or unstructured data sources.
• Hands-on experience with platforms and frameworks such as OpenAI, Azure OpenAI, Hugging Face, LangFlow, LangChain, and comparable technologies.
• Experience designing AI agents and RAG pipelines using vector databases such as Pinecone or knowledge-graph-backed solutions.
• The ability to build secure, scalable solutions using Microsoft Azure, with familiarity in Docker, Kubernetes, and continuous integration and continuous delivery (CI/CD). Experience with Azure AI Studio, Azure Cognitive Search, and Azure Cosmos DB is preferred.
• Experience creating and maintaining LLM evaluation frameworks using tools such as Promptfoo, OpenAI Evals, or LangSmith.
• Experienc…