Florence Healthcare - US

Florence Healthcare - US

Senior AI Engineer

Atlanta, GA · Senior

Sponsorship not specifiedDetected 27 days ago
Code ReviewLLMsRAGA/B TestingSystems EngineeringResearchCommunicationCollaboration

About the role

  • What We Do: Florence software advances cures by helping the world's most important research sites do their best work.
  • 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.

Responsibilities

  • Design and implement AI-powered features (LLM workflows, copilots, and agent-based systems with tool use and multi-step reasoning)
  • Ships high-quality AI features that deliver clear user value
  • Join our high-output culture to create innovative, modern, and purposeful software solutions.

Nice to have

  • Strong understanding of LLM capabilities and limitations
  • Experience with prompt engineering and structured output design
  • Hands-on experience with embeddings and vector search
  • Familiarity with RAG architectures and when to apply them
  • Experience designing agent-based architectures (AgentCore concepts)
  • Understanding of tool use, planning strategies, and memory mechanisms in LLM systems
  • 4+ years of related work experience
  • Evaluate agent performance across multi-step tasks (task success rate, error propagation)

Skills

  • Prompt pipelines for specific use cases
  • Retrieval systems (embeddings, chunking, ranking)
  • RAG-based workflows where needed
  • Iterate on outputs to improve quality, accuracy, and consistency
  • Select and evaluate models (hosted vs open-source) based on use case constraints
  • Agent-Based Systems (AgentCore)
  • Manage context, memory, and state across multi-step interactions
  • Balance deterministic workflows vs. agent autonomy for reliability and control
  • Run structured experiments to compare approaches (prompting, retrieval, models)
  • Define and track key metrics for AI performance (quality, latency, cost)
  • Debug and improve non-deterministic system behavior
  • Build and maintain evaluation datasets and benchmarks

Compensation

  • We offer a competitive compensation package, medical and dental insurance, and office space in the heart of the city.

Benefits

  • Do well. We offer a competitive compensation package, medical and dental insurance, and office space in the heart of the city.
  • We insist that health technology is the highest calling for software development.

Company info

  • 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.
  • 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:
  • We are looking for a Senior AI Engineer to design, build, and deploy high-quality AI-powered features.
  • This role focuses on owning end-to-end implementation of AI systems within a product area - from prototyping to production - with a strong emphasis on reliability, iteration, and measurable impact.
  • You will work closely with product and engineering teams to turn ambiguous problems into effective AI solutions, while contributing to best practices and raising the bar for AI development.
  • End-to-End AI Feature Ownership
  • Own the full lifecycle: prototyping → evaluation → production deployment → iteration
  • Ensure solutions are reliable, performant, and aligned with product needs
  • AI System Implementation
  • Build and optimize:
  • Design scalable and cost-efficient AI architectures for production workloads
  • Design and build agentic workflows capable of multi-step reasoning and decision-making
  • Integrate agents with tools, APIs, and internal systems to perform real-world actions
  • Implement planning, execution, and reflection loops for complex tasks
  • Experimentation & Evaluation
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