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.Job Description
Roles/Responsibilities
- 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.
- 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.
Eligibility Requirements
- 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
We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership –always with unyielding integrity.
We will not sponsor individuals for employment visas, now or in the future, for this job opening.GE HealthCare offers a great work environment, professional development, challenging careers, and competitive compensation. GE HealthCare is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE HealthCare will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
While GE HealthCare does not currently require U.S. employees to be vaccinated against COVID-19, some GE HealthCare customers have vaccination mandates that may apply to certain GE HealthCare employees.
Relocation Assistance Provided: Yes
Skills Required
- Bachelor's degree in Computer Science or a related discipline
- 4+ years of professional software development experience across the stack, including front-end engineering and modern design principles
- 1+ year of experience building scalable, distributed systems using AWS, Azure, or GCP and containerized deployments such as Docker, Kubernetes, or OpenShift
- Strong experience with Java and a modern Java microservice framework such as Quarkus or Spring Boot, plus JPA, Hibernate, or an equivalent backend stack
- Hands-on experience integrating third-party or partner APIs using REST, GraphQL, or webhooks, including OAuth 2.0 or OIDC authentication flows
- Hands-on experience building applications that call AI/ML services or large language model APIs
- 6+ years of professional software development experience
- Master's or PhD degree in Computer Science, Computer Engineering, or a related field
- Experience with retrieval-augmented generation, embeddings, vector databases, function and tool calling, agentic workflows, and prompt or context management
- Experience with MLOps model versioning, deployment, A/B testing, and offline or online model evaluation
- Experience building integrations using FHIR, HL7, DICOM, or SMART on FHIR authorization
- Experience designing partner-facing API contracts, developer ecosystems, marketplaces, or application stores
- Experience with event-driven architecture, message queues, and idempotent, fault-tolerant integration patterns
- Familiarity with data privacy, PHI handling, HIPAA, GDPR, and regulatory considerations for AI and third-party data flows
- Experience designing large-scale distributed systems, preferably using AWS
- Experience with big data systems, analytics, containerized microservices, and serverless functions
- Experience supporting production software deployments
- Experience creating, documenting, and communicating software architectures for complex products
- Experience working directly with end customers or partners to assess needs, identify solutions, and resolve disagreements
- Experience building, tracking, and communicating plans within Agile processes
- Experience working in regulated or safety-critical software environments such as healthcare, medical devices, or pharmaceuticals
- Legal authorization to work in the United States without employment visa sponsorship
GE Healthcare Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about GE Healthcare and has not been reviewed or approved by GE Healthcare.
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Healthcare Strength — Healthcare coverage is portrayed as comprehensive, including medical, dental, and vision options with HSA-eligible choices and preventive care coverage. Mental health and well-being support programs are also emphasized as part of the overall package.
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Retirement Support — Retirement support is described as meaningful, with a 401(k) match and additional programs such as student-loan matching in some descriptions. Legacy pension and retiree medical obligations for certain closed groups also signal continued support for long-tenured populations.
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Strong & Reliable Incentives — Variable and role-linked earning opportunities appear attractive in some job families, including high on-target earnings potential in certain sales roles. Additional role-based perks like company cars and travel-related reimbursements further increase the perceived value of total rewards in those positions.
GE Healthcare Insights
What We Do
Every day millions of people feel the impact of our intelligent devices, advanced analytics and artificial intelligence. As a leading global medical technology and digital solutions innovator, GE Healthcare enables clinicians to make faster, more informed decisions through intelligent devices, data analytics, applications and services, supported by its Edison intelligence platform. With over 100 years of healthcare industry experience and around 50,000 employees globally, the company operates at the center of an ecosystem working toward precision health, digitizing healthcare, helping drive productivity and improve outcomes for patients, providers, health systems and researchers around the world. We embrace a culture of respect, transparency, integrity and diversity.
