Job Description

Summary

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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.

As the Senior AI Application Engineer, 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.

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Role Overview

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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.


As the Senior AI Application Engineer, 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.

Core Responsibilities

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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.

Experience Requirements

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Education:

Master's degree (or equivalent experience) in Computer Science, Software Engineering, Artificial Intelligence, or related STEM field.

Experience:

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.

Additional Information

==========================

Relocation Assistance Provided:

Yes