GE HealthCare

Staff AI Application Engineer, Enterprise AI

GE HealthCare

full-time

Posted on:

Location Type: Hybrid

Location: Krakow • 🇵🇱 Poland

Visit company website
✨ AI Apply
Apply

Job Level

Lead

Tech Stack

AWSAzureCloudDockerFlaskGoogle Cloud PlatformGraphQLGRPCJavaScriptKubernetesMicroservicesNext.jsNode.jsPythonPyTorchReactSDLCTensorflowTypeScript

About the role

  • Design and Develop: AI-powered applications, integrating machine learning and generative models into enterprise-grade software products and internal tools.
  • Owning the full software development lifecycle (SDLC), including unit, integration, and end-to-end testing.
  • Frontend: Developing modern, intuitive interfaces for AI applications (React/Next.js, TypeScript, or equivalent) with a strong focus on usability, accessibility, and AI explainability.
  • Backend: Implementing scalable and secure back-end services (FastAPI, Flask, or Node.js) to expose AI capabilities (LLMs, RAG pipelines, AI agents) through standardized APIs.
  • Translating data science prototypes and GenAI models (LLMs, diffusion models, transformers) into scalable applications or services with intuitive user interfaces and reliable back-end infrastructure.
  • Collaborating with Insight Leaders and business stakeholders on requirements gathering, project documentation, and development planning.
  • Partnering with MLOps and GenAIOps teams to deploy, monitor, and continuously improve AI applications within standardized CI/CD pipelines.
  • Designing and implementing integrations using REST, GraphQL, and gRPC; work with cloud-based AI APIs (Azure, AWS, GCP) and enterprise data sources.
  • Integrating cloud-native AI services (AWS Bedrock, Azure OpenAI) and open-source frameworks (LangChain, LangGraph) into enterprise environments.
  • Monitoring application performance and user adoption, iterating on models and workflows to enhance usability and business impact.
  • Optimizing application performance, infrastructure efficiency, and LLM utilization.
  • Documenting 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.
  • 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
  • Relocation Assistance Provided

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
PythonTypeScriptJavaScriptReactNext.jsFastAPIFlaskTensorFlowPyTorchDocker
Soft skills
collaborationcommunicationmentoringproblem-solvingdebugginganalytical skills
Certifications
Master’s degreePhD