AI Engineer

Ironclad is the leading AI contracting platform that transforms agreements into assets. Contracts move faster, insights surface instantly, and agents push work forward, all with you in control. Whether you’re buying or selling, Ironclad unifies the entire process on one intelligent platform, providing leaders with the visibility they need to stay one step ahead. That’s why the world’s most transformative organizations, from OpenAI to the World Health Organization and the Associated Press, trust Ironclad to accelerate their business.

We’re consistently recognized as a leader in the industry: a Leader in the Forrester Wave and Gartner Magic Quadrant for Contract Lifecycle Management, a Fortune Great Place to Work, and one of Fast Company’s Most Innovative Workplaces. Ironclad has also been named to Forbes’ AI 50 and Business Insider’s list of Companies to Bet Your Career On. We’re backed by leading investors including Accel, Y Combinator, Sequoia, BOND, and Franklin Templeton.

This is a hybrid role. Office attendance is required at least twice a week on Tuesdays and Thursdays for collaboration and connection. There may be additional in-office days for team or company events.

eleni Ironclad is accelerating its AI initiatives to transform how legal teams manage contracts. We're looking for a AI/ML Engineer to help shape the future of legal AI. In this role, you’ll work with cutting‑edge tools such as Hugging Face, OpenAI APIs, and Rivet to develop state‑of‑the‑art models and intelligent systems that extract structured insights from contracts and power product features used by leading legal teams.

You’ll partner closely with product managers and designers to translate user needs into AI‑powered product capabilities. You’ll also lead efforts in model evaluation, iteration, and deployment—ensuring our systems are robust, explainable, and continuously improving. As part of our end‑to‑end ownership model, you’ll contributeiginal to the MLOps stack to ensure our models are scalable, reliable, and performant in production.

• Build and tune models and AI capabilities that ingest legal documents, extract key information, and deliver actionable insights to customers
• Implement backend services that power document understanding, classification, and natural language search
• Explore and apply cutting‑edge techniques in NLP, LLM integration, Prompt / Context Engineering, and semantic search to advance Ironclad’s AI/ML vision
• Design and maintain robust systems for prompt management, model training / tuning, orchestration, evaluation & inference, with a focus on scalability, reliability, and observability
• Develop and scale retrieval‑augmented generation (RAG) systems and agent‑based orchestration frameworks for complex legal workflows
• Help build foundational AI/ML infrastructure, including tools for experimentation, model versioning, and online/offline performance monitoring
• Partner closely with product managers and designers to shape user‑facing AI experiences and deliver value through APIs and intelligent features

• BS degree in Computer Science, Engineering, or a related field
• Experience working with large language models (e.g., GPT, Claude) or building RAG systems
• Experience with embedding models and vector databases
• Experience in training, evaluating, and serving machine learning models
• Hands‑on experience with Python, backend service development, and RESTful APIs
• Experience in NLP techniques such as text classification, entity extraction, document understanding, or question answering
• Proficiency with AI frameworks and APIs (e.g., PyTorch, Tensor Flow, Hugging Face, OpenAI, Lang Chain)
• Experience with cloud platforms (e.g., GCP, AWS, Azure)
• Solid understanding of Git or other version control systems
• Strong engineering fundamentals and attention to code quality, testing, and maintainability
• Excellent communication and collaboration skills
• Passion for building AI products that solve real‑world customer problems

• Familiar
  923er with Vertex AI or other managed ML platforms
• Experience working with PDF and DOCX parsing for document ingestion
• Comfort with Docker and…