About the job
At Ironclad, we are revolutionizing the way organizations manage their contracts through our leading AI contracting platform. Our technology transforms agreements into valuable assets, allowing contracts to move swiftly, insights to surface instantly, and agents to drive work forward—all while you maintain control. Whether buying or selling, Ironclad streamlines the entire process on a single intelligent platform, empowering leaders with the visibility they need to stay ahead of the curve. Esteemed organizations like OpenAI, the World Health Organization, and the Associated Press rely on Ironclad to enhance their business operations.
We are consistently recognized as a leader in our field, being named a Leader in the Forrester Wave and the Gartner Magic Quadrant for Contract Lifecycle Management, as well as one of Fortune's Great Places to Work and Fast Company’s Most Innovative Workplaces. Additionally, Ironclad has been featured in Forbes’ AI 50 and Business Insider’s list of Companies to Bet Your Career On. Our growth is supported by top-tier investors including Accel, Y Combinator, Sequoia, BOND, and Franklin Templeton. Visit us at www.ironcladapp.com or connect with us on LinkedIn.
Please note: This is a hybrid role. Attendance in the office is required at least twice a week on Tuesdays and Thursdays for collaboration and connection, with additional in-office days for team or company events.
AI Engineering at Ironclad
We are accelerating our AI initiatives to reshape how legal teams operate with contracts. We are seeking a skilled AI/ML Engineer to play a critical role in defining the future of legal AI. In this position, you will utilize advanced tools such as HuggingFace, OpenAI APIs, and Rivet to develop state-of-the-art models and intelligent systems that derive structured insights from contracts and enhance product features utilized by top legal teams.
You will collaborate closely with product managers and designers to convert user requirements into AI-driven product functionalities. Additionally, you will lead initiatives in model evaluation, iteration, and deployment, ensuring our systems are robust, explainable, and consistently improving. As part of our end-to-end ownership model, you will contribute to the MLOps stack to guarantee our models are scalable, reliable, and high-performing in production.

