About The Position

GE HealthCare is accelerating its transformation through a series of strategic “AI Big Bets” in Commercial excellence, Logistics optimization, Inventory management, and Manufacturing innovation. The Enterprise AI team, part of the Chief Data and Analytics Office, is at the forefront of delivering robust, enterprise-grade AI and ML solutions that drive measurable business impact at scale. GE HealthCare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world. Job Description You will be at the forefront of developing and delivering innovative GenAI and Agentic AI solutions that generate actionable business insights and transform key areas within GE HealthCare, including Finance, Commercial, Supply Chain, Quality, Operational Excellence and Lean, and Manufacturing. We are seeking a highly skilled and motivated AI Application Engineer to join our dynamic team. You will play a pivotal role in shaping and executing our AI strategy. You’ll collaborate across a unified, cross-functional delivery organization—partnering with experts in data engineering, ML engineering, analytics, and GenAI development—to solve complex business challenges and deliver scalable solutions.

Requirements

  • Bachelors degree in Computer Science, Software Engineering, Artificial Intelligence, or related STEM field.
  • 5+ years of experience architecting, building, and scaling complex AI/GenAI systems in enterprise or regulated environments.
  • Expertise in Python, and full-stack engineering for AI — capable of leading architecture across front end, back end, and model integration.
  • Mastery of LLMs, diffusion models, RAG architectures, and multi-agent (A2A) systems, with demonstrated implementation in production.
  • Hands-on experience designing multi-model orchestration and context management using MCP or equivalent protocols / frameworks.
  • Deep understanding of LLMOps/GenAIOps platforms and pipelines, enabling robust observability, versioning, and continuous learning cycles.
  • Proficiency in cloud architecture design (AWS, Azure), including cost optimization, scaling, and secure data governance.
  • Expertise in software architecture patterns (microservices, event-driven, serverless) and API ecosystems (REST, gRPC).
  • Proven leadership in AI security, governance, and compliance, ensuring full auditability and traceability.
  • Drives innovation through research translation, proof-of-concept leadership, and collaboration with Data Science, Ops, Product, and Platform teams.
  • Outstanding ability to communicate technical vision to executives and lead strategic AI initiatives across global teams.

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.

Benefits

  • Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities.
  • Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration, and support
  • GE HealthCare offers a competitive benefits package, including not but limited to medical, dental, vision, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, and tuition reimbursement.
  • GE HealthCare offers a great work environment, professional development, challenging careers, and competitive compensation.
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