Job description

Job Description Summary As an Applied AI & Integration Engineer for our Science and Technology Organization, you’ll work across the full stack with a focus on two things: bringing artificial intelligence capabilities into production applications, and connecting our products to the third party platforms, partner applications, and external data sources our customers depend on. You’ll scope and lead complex technical projects, laying the groundwork for early-stage products to iterate and scale, while driving software engineering best practices and delivering high quality software on tight schedules. The work will be part of, but not limited to, the projects that are part of the recently created Wisconsin Tech Hub. At GE HealthCare, we are committed to bringing cloud-based solutions for our customers: all aspects of computing services across the cloud and edge – including servers, databases, storage, networking, analytics, software, intelligence are delivered over the Internet. Our Science & Technology organization is harnessing the power of technology to make healthcare more precise, more personalized, and more accessible for everyone. From driving the overall clinical research and patient-centric innovation strategy to delivering new digital and machine learning capabilities – we’re committed to leading digital transformation, improving outcomes for patients and providers, and creating a world where healthcare has no limits Job Description Roles/Responsibilities Work with a cross functional team to create software products under approved architecture and under the roadmap set by the product management team Take ownership of features end to end across the stack – user-facing interfaces, APIs, services, and data pipelines – with high emphasis on quality, test-driven development, and sound software engineering practices Design, build, and maintain integrations with third party platforms, partner applications, and external data sources, including authentication, authorization, rate limiting, retries, error handling, and version management Build and maintain the public APIs, SDKs, and connectors that third parties use to extend our products, along with the reference documentation and sample code that go with them Integrate AI and machine learning capabilities into production applications, including model serving endpoints, large language model and retrieval-augmented generation (RAG) workflows, and inference pipelines Establish evaluation harnesses, guardrails, and monitoring for AI features covering accuracy, latency, cost, drift, and safe behavior in production Partner with data science and clinical teams to move models from prototype to a supportable, observable production service Participate in software design reviews, conduct peer code reviews, and provide input and feedback to other members of the development team Use software engineering best practices to ensure a high standard of quality for all the team deliverables Minimum Qualifications Bachelor’s degree in Computer Science or related discipline 4 years of professional software development experience across the stack including front end engineering and modern design principles 1 year of experience with building scalable, distributed systems using a modern cloud framework such as AWS, Azure or GCP and containerized deployments (Docker, Kubernetes/OpenShift) Strong experience with Java, a modern Java microservice framework (Quarkus, Spring Boot), JPA (e.g. Hibernate) or an equivalent backend stack Hands-on experience integrating third party or partner APIs (REST, GraphQL, or webhooks), including OAuth 2.0 / OIDC authentication flows Hands-on experience building applications that call AI/ML services or large language model APIs Desired Qualifications 6 years of professional software development experience Master’s or PhD degree in Computer Science, Computer Engineering, or related field Experience with large language model application patterns: retrieval-augmented generation, embeddings and vector databases, function and tool calling, agentic workflows, and prompt and context management Experience with model lifecycle tooling (MLOps) including versioning, deployment, A/B testing, and offline and online evaluation of model quality Experience building integrations against healthcare interoperability standards such as FHIR, HL7, and DICOM, including 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 for unreliable external systems Familiarity with data privacy, PHI handling, and regulatory considerations (e.g. HIPAA, GDPR) as they apply to AI features and third party data flows Experience with design/architecting large-scale distributed systems preferably using AWS technologies Previous experience with big data systems, analytics, containerized microservices, and serverless functions Experience with supporting production software deployments Experience creating, documenting, and communicating software architectures for complex products Previous experience working directly with end customers or partners to assess needs, identify solutions, and constructively resolve disagreements Experience in building, tracking, and communicating plans within Agile processes Excellent technical problem-solving skills and aptitude to learn new technologies and methodologies Experience working in regulated or safety-critical software environments (healthcare, medical devices, pharmaceuticals, or similar) 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

Requirements

Must-haves

Job Description Roles/Responsibilities
Work with a cross functional team to create software products under approved architecture and under the roadmap set by the product management team
Take ownership of features end to end across the stack – user-facing interfaces, APIs, services, and data pipelines – with high emphasis on quality, test-driven development, and sound software engineering practices
Build and maintain the public APIs, SDKs, and connectors that third parties use to extend our products, along with the reference documentation and sample code that go with them
Integrate AI and machine learning capabilities into production applications, including model serving endpoints, large language model and retrieval-augmented generation (RAG) workflows, and inference pipelines
Establish evaluation harnesses, guardrails, and monitoring for AI features covering accuracy, latency, cost, drift, and safe behavior in production
Partner with data science and clinical teams to move models from prototype to a supportable, observable production service
Participate in software design reviews, conduct peer code reviews, and provide input and feedback to other members of the development team
Use software engineering best practices to ensure a high standard of quality for all the team deliverables
Bachelor’s degree in Computer Science or related discipline
4 years of professional software development experience across the stack including front end engineering and modern design principles
1 year of experience with building scalable, distributed systems using a modern cloud framework such as AWS, Azure or GCP and containerized deployments (Docker, Kubernetes/OpenShift)

Nice-to-haves

Master’s or PhD degree in Computer Science, Computer Engineering, or related field
Experience with large language model application patterns: retrieval-augmented generation, embeddings and vector databases, function and tool calling, agentic workflows, and prompt and context management
Experience with model lifecycle tooling (MLOps) including versioning, deployment, A/B testing, and offline and online evaluation of model quality
Experience building integrations against healthcare interoperability standards such as FHIR, HL7, and DICOM, including 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 for unreliable external systems
Familiarity with data privacy, PHI handling, and regulatory considerations (e.g. HIPAA, GDPR) as they apply to AI features and third party data flows
Experience with design/architecting large-scale distributed systems preferably using AWS technologies
Previous experience with big data systems, analytics, containerized microservices, and serverless functions
Experience with supporting production software deployments
Experience creating, documenting, and communicating software architectures for complex products
Previous experience working directly with end customers or partners to assess needs, identify solutions, and constructively resolve disagreements

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learninggoawsazuregcpdockerkubernetesjavarestgraphqlmlapiagile

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Professional Development