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Strong global brand, metro location, and broad AI/full-stack skill requirements increase candidate competition.
Skills in LLM integration, Python, TypeScript and platform engineering are broadly transferable across industries.
Many mandatory AI, full-stack, and tooling skills create strict shortlisting filters.
Develop and maintain GE HealthCare's internal AI engineering framework including reusable libraries, code generation tools, and automated verification to enable rapid, secure AI production.
Build selected end-to-end AI applications as pilots and reference implementations to validate platform capabilities.
Continuously evolve shared platform components ensuring semantic versioning, backward compatibility, and adherence to engineering standards through automation.
Bachelor's degree in Computer Science, Software Engineering, IT, or equivalent practical experience.
Strong proficiency in Python with static type checking and runtime validation; working knowledge of TypeScript and modern front-end frameworks (React, Vue, Angular).
Experience integrating large language models into production with agent frameworks and evaluation of non-deterministic AI systems using automated frameworks.
Familiarity with containerization (Docker), major cloud services (preferably AWS), infrastructure-as-code tools (Terraform, Pulumi, CloudFormation), and HTTP API design with strong experience in version control and CI/CD pipelines.
Experienced in balancing full-stack application development with platform and tooling engineering to enable other engineers and data scientists.
Skilled in building automation and strict validation tooling over documentation to enforce standards and accelerate deployment.
Practiced at maintaining long-lived shared platforms with strong emphasis on semantic versioning, automated compatibility tests, and progressive capability ownership based on real use cases.