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Senior AI Applications Engineer

GE HealthCare

Bengaluru

5-8 years

Today

$25.3K–38.6K/yr

Full-time

Onsite

Skills Required

LLM

RAG

LangChain

Embeddings

Ragas

AgentCore

AWS Bedrock

CrewAI

LangGraph vector search pgvector

FAISS

OpenSearch

Pinecone

DeepEval

Description

Seeking a full-stack engineer to build production applications and internal platform tooling for GE HealthCare's AI engineering framework, enabling rapid, secure, and compliant AI solution deployment.

Company: GE HealthCare

Role: Full-stack Engineer

Experience

- Practical experience building production applications
- Experience integrating large language models into production software
- Experience with at least one AI agent framework
- Experience evaluating non-deterministic systems
- Working knowledge of major public cloud services, ideally AWS
- Experience with containerisation (Docker)
- Experience reading and reviewing infrastructure-as-code (Terraform, Pulumi, CloudFormation)

Qualification

- Bachelor's degree in Computer Science, Software Engineering, IT or related field or equivalent practical experience
- Advanced degree welcome but not required

Responsibilities

- Build shared platform capabilities including reusable libraries, execution layer for AI agents, configuration-driven user interface, and data access layer
- Develop selected AI applications end to end as reference implementations and pilot use cases
- Build tooling such as code generation tools, automated verification in delivery pipelines, and machine-readable interfaces
- Maintain and evolve the platform with semantic versioning, migration paths, dependency upgrades, and continuous improvement
- Collaborate and support colleagues using the platform, review code, document design decisions, and express infrastructure requirements as version-controlled declarations

Additional Responsibilities

- Ensure correctness through automated tooling rather than expert human review




- Contain scope by adding shared capabilities only when demonstrated by multiple consumers
- Use AI coding assistants effectively and responsibly
- Interpret distributed traces and structured logs, define service level objectives and runbooks
- Maintain delivery security practices including immutable artefacts, build provenance, and short-lived federated credentials

Nice To Have

- Advanced degree
- Experience with AI evaluation frameworks (Ragas, DeepEval, LangFuse)
- Experience with retrieval-augmented generation technologies (pgvector, FAISS, OpenSearch, Pinecone)

More Skills Python with static type checking (mypy, Pyright) and runtime validation (Pydantic), TypeScript and up-to-date component-based front-end frameworks (React, Vue, Angular), HTTP API design and specification (OpenAPI), Relational databases and SQL, Version control and CI/CD (GitHub Actions, GitLab CI, Jenkins), Automated testing at unit, integration and interface-contract levels, AI and Generative AI engineering, AI agent frameworks (LangGraph, LangChain, AWS Bedrock AgentCore, CrewAI), Cloud services (AWS Lambda, S3, SQS, Aurora, RDS, Bedrock), Infrastructure-as-code (Terraform, Pulumi, CloudFormation), Distributed tracing and structured logs (OpenTelemetry, Datadog, Grafana), Security practices including secret scanning and dependency vulnerability management

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