Director of AI

What We Do:

Florence software advances cures by helping the world’s most important research sites do their best work. Our solutions are now used by over 65,000 research teams in 90 countries around the world—we’re the most widely deployed site workflow tool in the industry. By the end of the decade, we’ll double the pace at which new medicines get to market by doubling the output of trial site teams. To date, we were named a Deloitte Fast 50 business, G2 Category Leader, an Inc. & AJC best place to work, and an Inc. 5000 company five years in a row. 

At Florence, we are committed to make the world a better place by accelerating research while providing an environment for our employees where they can be happy in their lives, enjoy their jobs, and grow. 

What You’ll Bring to the Team:

The Director of AI leads the design, development, and delivery of AI-powered capabilities across Florence products. This is a hands-on technical leadership role responsible for guiding architecture, mentoring engineers, evaluating emerging AI technologies, and partnering closely with engineering teams to deliver scalable, production-ready AI solutions. While this role includes people leadership, success is measured by the ability to help teams solve complex technical challenges and accelerate the delivery of AI capabilities. 

You Will:

Technical Leadership & Architecture 

• Lead the technical design and architecture of AI-powered products and platforms.
• Evaluate and recommend LLMs, AI frameworks, orchestration platforms, and emerging AI technologies.
• Remain hands-on by building prototypes, validating technical approaches, and helping teams solve complex AI engineering challenges.
• Review architecture, code, and technical designs to ensure scalable, secure, and maintainable solutions.
• Guide engineers on best practices for Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, and model integration.
• Mentor AI engineers through technical coaching, design reviews, and pair problem-solving.

AI Engineering Delivery

• Lead the development and operationalization of machine learning pipelines, including data preparation, feature engineering, model training, validation, deployment, monitoring, and continuous improvement.
• Drive the best practices and adoption of MLOps practices to enable repeatable, scalable, and reliable machine learning model development and deployment across the organization.
• Work alongside engineering teams to unblock technical challenges and accelerate delivery.