AI Applied Health System Engineer
Rush University Medical Center
- Location
- Chicago, IL, US
- Track
- General AI
- Salary
- $85K–$129K / yr
- Posted
- October 8, 2026
- Source
- Indeed
Job description
Location: Chicago, Illinois
Business Unit: Rush Medical Center
Hospital: Rush University Medical Center
Department: D&IS Innovation
Work Type: Full Time (Total FTE between 0.9 and 1.0)
Shift: Shift 1
Work Schedule: 8 Hr (9:00:00 AM - 5:00:00 PM)
Rush offers exceptional rewards and benefits learn more at our Rush benefits page (https://www.rush.edu/rush-careers/employee-benefits).
Pay Range: $41.88 - $62.40 per hour
Rush salaries are determined by many factors including, but not limited to, education, job-related experience and skills, as well as internal equity and industry specific market data. The pay range for each role reflects Rush’s anticipated wage or salary reasonably expected to be offered for the position. Offers may vary depending on the circumstances of each case.
Summary
Rush University Medical Center is seeking an AI Applied Health System Engineer to develop and deploy innovative AI, Generative AI, and machine learning solutions that improve patient care, operational efficiency, clinical research, and revenue cycle performance. In this hands-on role, you'll work alongside clinicians, engineers, data scientists, and business leaders to transform complex healthcare challenges into scalable, real-world solutions.
From building GenAI applications and RAG pipelines to analyzing healthcare data and integrating AI into enterprise systems, you'll play a key role in advancing responsible AI adoption across one of the nation's leading academic health systems. If you're passionate about applying cutting-edge technology to solve meaningful healthcare problems, we'd love to hear from you.
Key Responsibilities
Applied AI & Solution Development
- Contribute to the design and development of AI, GenAI, and ML solutions for healthcare use cases, including data preparation, analytical modeling, prompt engineering, and RAG pipeline development
- Support implementation of AI use cases across clinical, financial, and operational domains
Assist in building, testing, and deploying AI solutions using Python and modern AI frameworks
Healthcare Data & System Integration
- Process and analyze structured and unstructured healthcare data (e.g., clinical notes, claims, EHR, ADT feeds) for AI/ML applications
Collaborate with engineers and data scientists to integrate AI solutions into existing health system platforms
Collaboration & Delivery
- Work closely with clinical stakeholders and business partners to understand requirements and translate them into technical solutions
- Support proof of concepts, pilots, and production deployments across healthcare domains
Participate in cross-functional teams to ensure solutions align with clinical workflows and organizational priorities
Quality, Governance & Documentation
- Contribute to testing, validation, and performance monitoring of AI models and applications
- Document workflows, methodologies, and technical solutions to enable scalability and knowledge transfer
Operate within established MLOps, governance, and compliance frameworks to ensure reliable and responsible AI solutions
Required Job
Qualifications
- Bachelor’s degree in Computer Science, Engineering, Data Science, Health Informatics, or a related field
- 3–5 years of experience in AI/ML, data science, or software engineering
- Experience working with Python and common AI/ML libraries
Strong analytical, problem-solving, and communication skills
Preferred Job
Qualifications
- Experience with healthcare data or working within a health system
- Familiarity with LLM frameworks (e.g., LangChain, LlamaIndex), RAG pipelines, embeddings, and vector databases
- Exposure to cloud platforms (Azure, AWS, or GCP) and ML tooling
- Understanding of healthcare workflows such as clinical operations, revenue cycle, or population health
- Familiarity with MLOps concepts including CI/CD, monitoring, and governance
Rush is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics.