Director of AI

Florence Healthcare; Atlanta (GA); On-site; USD 180,000 - 230,000; Full time

Job summary

Florence Healthcare in Atlanta, GA is seeking an AI Engineering Leader to drive the technical design and architecture of AI-powered products and platforms.

You will lead ML pipelines, MLOps, and collaborate with product teams to deliver reliable, scalable AI solutions that accelerate research and improve outcomes across sites.

Responsibilities

• 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.

Job description

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 30,000 research teams in 70 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.

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. Partner with Product Management to define and implement AI capabilities that solve customer problems. Ensure AI solutions are reliable, observable, performant, cost-efficient and production-ready. Balance rapid experimentation with engineering quality and operational excellence.