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# AI Applications Engineer

- **Company:** GE Healthcare
- **Location:** Brown Deer, WI, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Cloud Engineering, Computer Programming, Continuous Integration, Dicom, Medical Software, Interoperability, Python (Programming Language), Machine Learning, Language Modeling, Azure Machine Learning, Software Engineering, Fast Healthcare Interoperability Resources, Retrieval-Augmented Generation, Delivery Pipeline, Large Language Models, Multi-Agent Systems, Model Validation, Generative AI, Agentic-AI, Information Technology, Low Latency, Deployment Automation, Health Level Seven International, Machine Learning Operations, Artificial Intelligence Governance, Api Design, Restful APIs, Software Version Control
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ai-applications-engineer-milwaukee-wi--23517562-3fa4-4fe3-829e-a1ed085f8f68

## About the Role

Artificial Intelligence (AI), Software Engineering, Healthcare, Artificial Intelligence (AI), Software Engineering, Healthcare Software, Prototyping, Machine Learning, Modeling Languages, Application Programming Interface (API), * Bachelor''s degree in Computer Science, Engineering, or a related technical field.

 * 4+ years of software engineering, AI engineering, or machine learning engineering experience.
 * Hands-on experience building GenAI applications using LLMs, RAG, embeddings, vector databases, or agentic AI workflows.
 * Strong programming experience in Python and experience developing APIs and AI-powered services.
 * Demonstrated experience deploying and supporting AI/ML applications in production, including monitoring, evaluation, and operational reliability.
 * Experience integrating applications with REST APIs, third-party services, and enterprise data sources.
 * Experience with cloud-based AI/ML services and deployment environments (AWS, Azure, or GCP)., * Experience with MLOps/LLMOps tools and practices, including automated deployment, model evaluation, observability, and monitoring.
 * Experience with AI orchestration frameworks, agentic AI, function/tool calling, and production RAG architectures.
 * Experience implementing AI guardrails, responsible AI practices, and security controls.
 * Familiarity with healthcare interoperability standards (FHIR, HL7, DICOM) and healthcare data privacy requirements.
 * Experience delivering AI applications in regulated or enterprise environments., * GE HealthCare will only employ those who are legally authorized to work in the United States for this opening. We will not sponsor individuals for employment visas, now or in the future, for this job opening.
 * This role is based in the state of Wisconsin at the Waukesha facility of GE HealthCare

## Description

As an AI Applications Engineer within GE HealthCare''s Science & Technology Organization, you will design, build, and productionize AI-powered applications that improve healthcare workflows and product experiences.

This hands-on engineering role focuses on developing Generative AI (GenAI) applications, integrating AI capabilities with enterprise and third-party systems, and ensuring reliable, secure, and scalable production deployment. You will collaborate with AI scientists, product teams, and software engineers to bring AI solutions from prototype to production., * Design, develop, and deploy GenAI and machine learning applications using large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI workflows.

 * Productionize AI/ML solutions, including model serving, inference APIs, deployment pipelines, and integration into existing applications.
 * Implement MLOps/LLMOps practices for model versioning, CI/CD, testing, evaluation, monitoring, and lifecycle management.
 * Build evaluation frameworks, guardrails, and observability to improve AI application accuracy, reliability, latency, cost, and security.
 * Develop and maintain integrations with enterprise systems, third-party platforms, APIs, and external data sources.
 * Collaborate with cross-functional teams to translate product requirements and AI prototypes into reliable, production-ready solutions.