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Medium: strong employer brand plus specialized full-stack ML/platform skillset increases competition moderately.
High because role requires specialized ML/AI, agent frameworks, evaluation pipelines, and platform engineering experience.
High due to mandatory ML agent-framework, automated-evaluation, full-stack and platform engineering skill requirements.
Develop and maintain GE HealthCare's internal AI engineering framework including shared libraries, code generation tools, and automated verification systems supporting data scientists and engineers.
Build selected AI applications end to end (front end, back end, agents) as reference implementations and pilot use cases to validate and evolve platform capabilities.
Continuously improve platform dependability by managing interfaces, updating dependencies, enhancing documentation, and supporting platform users through tooling and code reviews.
Strong proficiency in Python with static type checking and runtime validation; experience with TypeScript and modern front-end frameworks (React, Vue, Angular).
Experience integrating large language models into production and using AI agent frameworks (e.g., LangGraph, LangChain).
Familiarity with cloud services (preferably AWS) including serverless compute, object storage, messaging, managed databases, and AI model services.
Work Experience Required: Not explicitly mentioned in the JD; bachelor's degree in Computer Science or equivalent practical experience required.
Engineer with strong cross-functional skills combining full-stack application development and platform/tooling engineering focused on scalable AI solutions.
Experienced in automating correctness through tooling (type systems, code generation, automated verification) rather than relying on manual expert review.
Capable of working with complex AI production systems, managing versioned APIs and interfaces, and maintaining long-term platform stability and usability for data science teams.