Staff AI Application Engineer, Enterprise AI

3 days ago

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GE HealthCare

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Healthcare • Medical Technology • Pharmaceuticals

GE HealthCare is a leader in precision care, dedicated to providing innovative technologies and integrated solutions that enhance healthcare services. As a stand-alone company, it focuses on imaging, ultrasound, and healthcare IT, empowering clinicians and improving patient outcomes through advanced medical technologies and personalized care solutions. With a significant investment in research and development, GE HealthCare aims to transform healthcare by making hospitals more efficient and therapies more precise.

10,000+ employees

Founded 1892

💊 Pharmaceuticals

📋 Description

• 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 or PhD degree (or equivalent experience) in Computer Science, Software Engineering, Artificial Intelligence, or related STEM field. • 3–5 years of hands-on experience developing and deploying AI-powered or data-driven applications in enterprise environments. • Advanced proficiency in Python, plus strong working knowledge of TypeScript/JavaScript and at least one modern web framework (React, Next.js, FastAPI, Flask). • Proven track record implementing end-to-end AI systems, integrating ML/LLM models into scalable microservices or enterprise applications. • Strong experience in ML/GenAI frameworks (TensorFlow, PyTorch, LangChain, AutoGen, Semantic Kernel) and cloud-native AI platforms (AWS Bedrock, Azure OpenAI). • Working knowledge of cloud environments (AWS, Azure, or GCP) and containerization tools (Docker). • Deep experience with Docker, Kubernetes, and CI/CD automation for AI workloads. • Demonstrated experience with RAG pipelines, vector databases, and document retrieval frameworks. • Solid understanding of LLMOps / GenAIOps integration patterns, model evaluation, and prompt optimization workflows. • Strong collaboration skills and the ability to communicate effectively within cross-functional teams. • 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.

🏖️ Benefits

• Healthcare solutions • Medical technology • Intelligent devices • Advanced technology tools