Overview
Senior Staff AI Application Engineer responsible for GE HealthCare’s internal AI engineering platform, including architecture, shared libraries/interfaces, code generation tools, and automated verification used to take AI solutions to production.
What you'll do
- Define platform architecture and public interfaces, including what’s offered/guaranteed and versioning promises.
- Design replaceable isolation boundaries for components like agent frameworks, model providers, queues, data sources, and UI rendering.
- Establish interfaces as machine-readable specifications with automated verification to enable reliable cross-team integration.
- Lead high-leverage platform delivery including the agent execution layer, secure data resolution layer, and configuration-driven UI system.
- Build AI applications end to end (front end, back end, agents) when it best proves platform capability or unblocks use cases.
- Own backward compatibility, versioning, migration, deprecation, and prevention of version divergence across dependent solutions.
- Define version-controlled interfaces with adjacent disciplines (infrastructure, security, data) with automated validation.
What you'll need
- Minimum 8 years of professional software engineering experience with ownership of a shared library/framework/SDK/internal developer platform relied on by other engineering teams.
- Advanced Python for static and structural typing (mypy or Pyright, strict), interface definition, and type-earn-cost judgement.
- Strong TypeScript and modern component-based front-end engineering (React) to design typed component contracts and a design token system.
- API and interface design skills including OpenAPI specifications, generated clients, versioning, compatibility, and deprecation.
- Deep relational database and SQL knowledge including schema design, migrations, indexing, load behavior, and injection resistance.
- Testing and CI/CD design across unit, integration, interface-contract, and end-to-end with reusable pipeline components (GitHub Actions/GitLab CI).
- Substantial production experience with LLM systems including instruction design, tool/function calling, structured output, RAG and evaluation-driven development as a release gate.
Details
- Location is Bengaluru, Karnataka, India (ATS: IND19-01-Bengaluru-EPIP 122 (Phase II)).
Read the full description and apply on the company’s own careers page.
