Staff Ai Engineer

GE HealthCare

Hybrid
Generative ai / llms
Rag pipelines
Knowledge graph / graph rag
Build and deploy production-grade Generative AI systems in a MedTech environment, translating real-world workflows into scalable, reliable AI-powered applications

Job Summary

  • Build and deploy production-grade Generative AI systems in a MedTech environment, translating real-world workflows into scalable, reliable AI-powered applications.
  • Design, build, integrate, and operate LLM-based systems including RAG, Knowledge Graphs, Graph RAG, and Agentic AI workflows on AWS using SageMaker and Bedrock.
  • Work embedded with stakeholders to understand workflows, validate AI outputs, and iterate quickly from prototype to production, owning solutions in production including monitoring, debugging, and continuous improvement.

Matching Summary

Build and deploy production-grade Generative AI systems in a MedTech environment, translating real-world workflows into scalable, reliable AI-powered applications.

Skills & Requirements

Must-have

  • Generative AI / LLMs
  • RAG pipelines
  • Knowledge Graph / Graph RAG
  • Agentic AI systems
  • AWS SageMaker and Bedrock
  • Python backend services and APIs
  • CI/CD and MLOps practices

Nice-to-have

  • system design fundamentals
  • observability and security
  • customer-facing environments
  • business acumen
  • global teams
  • mentoring team members

Key Requirements

  • Bachelor's Degree in Computer Science or STEM
  • basic experience
  • Proficiency in Python
  • Hands-on experience with Generative AI / LLMs
  • Experience deploying and operating systems on AWS

Work Rights

Not specified

Tailored Resume

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