AI Engineer (LLMs for Healthcare)

keeblerhealth; United States; On-site; USD 120,000 - 190,000; Full time

Job summary

Keebler Health is seeking a mid to senior level AI Engineer to build and fine-tune large language models for healthcare workflows. You will design robust AI solutions with RAG, knowledge graphs, and compliant deployment while collaborating closely with clinicians to improve care outcomes.

The role emphasizes production-grade MLOps, scalable pipelines, and ongoing innovation in AI for value-based care in the U.S. market.

Qualifications

• Proven experience in LLM fine-tuning and advanced prompt engineering.
• Strong background in Python and modern ML frameworks (HuggingFace, PyTorch).
• Familiarity with HIPAA, FHIR healthcare standards.
• Hands-on experience with Retrieval-Augmented Generation (RAG).
• Experience with MLOps frameworks such as MLflow or Langfuse.
• Cloud and containerization in AWS/GCP/Azure; Docker/Kubernetes.

Responsibilities

• Fine-tune and optimize large language models for healthcare applications.
• Develop and apply prompt engineering for clinical scenarios.
• Implement RAG to improve knowledge retrieval.
• Work with knowledge graphs to organize healthcare data.
• Evaluate models with precision, recall, and reliability.
• Collaborate with clinicians to align AI with workflows.
• Deploy and monitor AI models in production; ensure HIPAA compliance.

Skills

LLM fine-tuning

Prompt engineering

Python

Healthcare workflows

HIPAA & FHIR awareness

Collaboration with clinicians

Problem solving

Education

Bachelor's degree in Computer Science/Engineering or related field

Tools

HuggingFace

PyTorch

MLflow

Docker

Kubernetes

AWS/GCP/Azure

Job description

About Keebler Health

Keebler Health is building the operating system for value-based care. Our mission is to help risk-bearing healthcare organizations thrive in value-based arrangements by unlocking the full power of their data. We empower leading primary care groups, ACOs, and health plans to act on real-time insights that improve outcomes, reduce costs, and fuel sustainable growth.

We're a fast-moving, high-performing team, and we’re looking for people who share our bias toward speed, urgency, and excellence. As a member of the team, you won’t just write code or stay in your lane—you’ll shape critical systems, innovate quickly, and set a high bar for a product that supports the future of U.S. healthcare.

About the role

We are seeking a talented and motivated mid to senior level AI Engineer with expertise in developing and fine-tuning large language models (LLMs), healthcare workflows, and AI/ML engineering best practices. The ideal candidate will bring a deep understanding of healthcare-specific challenges and modern AI techniques to drive innovation in Value-Based Care solutions. Level and salary will commensurate with experience.

Key Responsibilities

AI/ML Engineering

• Fine-tune and optimize large language models (LLMs) to address specific healthcare applications.
• Develop and apply advanced prompt engineering techniques to enhance model outputs for clinical scenarios.
• Implement Retrieval-Augmented Generation (RAG) systems to improve knowledge retrieval from large datasets.
• Work with knowledge graphs to organize and integrate healthcare-specific data for enhanced decision-making.
• Evaluate black-box models using precision, recall, and other performance metrics, ensuring robustness and reliability.

Healthcare Expertise

• Collaborate with healthcare professionals to understand workflows and identify opportunities for AI-driven enhancements.
• Design and build AI models that align with healthcare standards and regulations (e.g., HIPAA compliance).
• Integrate domain-specific knowledge of healthcare data, including FHIR and interoperability standards, into AI solutions.

MLOps & Deployment

• Develop and maintain scalable, production-ready AI pipelines using MLOps tools.
• Deploy and monitor AI models in production environments to ensure performance and compliance.
• Optimize infrastructure for efficient training, testing, and deployment of models.

Innovation and Optimization

• Stay at the forefront of advancements in AI, especially in healthcare applications.
• Identify and resolve performance bottlenecks in AI workflows.
• Explore emerging trends and technologies in LLMs and healthcare to continually improve solutions.

Collaboration and Impact

• Partner with cross-functional teams, including data engineers and clinicians, to ensure seamless integration of AI into healthcare workflows.
• Communicate technical results and insights effectively to non-technical stakeholders.

Required Qualifications

• Proven experience in LLM fine-tuning and advanced prompt engineering.
• Strong background in Python and modern ML frameworks (e.g., Huggingface, pyTorch).
• Familiarity with healthcare workflows and regulatory requirements (e.g., HIPAA, FHIR standards).
• Hands-on experience with retrieval-augmented generation (RAG) techniques.
• Expertise in evaluating AI models using performance metrics like precision, and recall.

Preferred Skills

• Experience with MLOps frameworks such as MLflow, Langfuse, or similar tools.
• Understanding of healthcare data standards, including HL7 and HEDIS metrics.
• Strong problem-solving skills in integrating AI with complex healthcare datasets.
• Familiarity with cloud platforms (e.g., AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

What We Offer

• Competitive salary and benefits package.
• Opportunity to work in a fast-paced, innovative environment.
• Professional growth and development opportunities.
• Collaborative and supportive team culture.
• Chance to make a meaningful impact on the healthcare industry.