Senior AI Applications Engineer
GE HealthCare (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 30–55 LPA
Posted on 2 Sept
Reach people at GE HealthCare
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at GE HealthCare you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- 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.
Minimum Requirements
- 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.
Ideal Candidate Profile
- 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.