GE HealthCareRemote
Senior AI Application Engineer, Enterprise AI
United States
Full-time
5 hours ago
H1B Sponsor Likely
Key skills
JavaScriptTypeScriptPythonAIArtificial IntelligenceMachine LearningMLGenAILLMOpenAIPyTorchTensorFlowHugging FaceLangChainMLOpsLangGraphPineconeAnalyticsReactNext.jsNode.jsFastAPIFlaskGraphQLgRPCAWSAzureGCPDockerBedrockRESTfulGitVersion ControlAgileSDLCCI/CDCommunicationCollaboration
About this role
GE HealthCare is accelerating its transformation through strategic AI initiatives, focusing on delivering enterprise-grade AI and ML solutions. As a Senior AI Application Engineer, you will develop innovative GenAI and Agentic AI solutions, collaborating with cross-functional teams to address complex business challenges and enhance operational efficiency.
Responsibilities:
- Design and develop AI-powered applications, integrating machine learning and generative models into enterprise-grade software products and internal tools. Own the full software development lifecycle (SDLC), including unit, integration, and end-to-end testing
- Frontend: Develop modern, intuitive interfaces for AI applications (React/Next.js, TypeScript, or equivalent) with a strong focus on usability, accessibility, and AI explainability
- Backend: Implement scalable and secure back-end services (FastAPI, Flask, or Node.js) to expose AI capabilities (LLMs, RAG pipelines, AI agents) through standardized APIs
- Translate data science prototypes and GenAI models (LLMs, diffusion models, transformers) into scalable applications or services with intuitive user interfaces and reliable back-end infrastructure
- Collaborate with insight leaders and business stakeholders on requirements gathering, project documentation, and development planning
- Partners with MLOps and GenAIOps teams to deploy, monitor, and continuously improve AI applications within standardized CI/CD pipelines
- Design and implement integrations using REST, GraphQL, and gRPC; work with cloud-based AI APIs (Azure, AWS, GCP) and enterprise data sources
- Integrate cloud-native AI services (AWS Bedrock, Azure OpenAI) and open-source frameworks (LangChain, LangGraph) into enterprise environments
- Monitor application performance and user adoption, iterating on models and workflows to enhance usability and business impact
- Optimize application performance, infrastructure efficiency, and LLM utilization
- Document architectures, APIs, and deployment processes to ensure transparency, reusability, and maintainability
Requirements:
- Master's degree (or equivalent experience) in Computer Science, Software Engineering, Artificial Intelligence, or related STEM field
- 1–3 years of hands-on experience developing and deploying AI-powered or data-driven applications in production environments
- Strong proficiency in Python, with working knowledge of TypeScript/JavaScript for front-end or back-end integrations
- Practical experience with ML and GenAI frameworks such as TensorFlow, PyTorch, or Hugging Face
- Basic familiarity with LangChain, OpenAI API, or similar LLM toolkits
- Experience developing RESTful APIs for AI or analytics services
- Working knowledge of cloud environments (AWS, Azure, or GCP) and containerization tools (Docker)
- Exposure to RAG concepts, embeddings, or vector databases (e.g., Pinecone, FAISS)
- Understanding of fundamental software engineering practices — CI/CD, testing, version control (Git), code reviews, and agile methodologies
- Strong collaboration skills and the ability to communicate effectively within cross-functional teams
- Basic understanding of prompt engineering and model evaluation techniques
- Ability to mentor junior engineers, perform code reviews, and contribute to architectural decisions
- Strong problem-solving, debugging, and analytical skills, with clear and persuasive communication to technical and business audiences