- The engineer will use Google Cloud Platform (GCP), specifically Vertex AI and Gemini, to transform unstructured medical data into insights.

- Business objective is to improve claim accuracy and adjudication speed.

Key Responsibilities :

- Design and implement production-ready AI agents and workflows using Gemini (Pro/Flash) and Vertex AI Agent Builder to automate health claim validation.

- Utilize Document AI and Vertex AI Vision to extract and structure data from medical documents, such as patient charts and lab reports.

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines using Vertex AI Search and Conversation to cross-reference claims against insurance policy details and medical codes.

- Perform prompt engineering, fine-tuning, and performance monitoring to ensure AI outputs meet healthcare standards (e., IRDAI compliance).

- Develop and deploy scalable AI APIs using Cloud Run, GKE, or Cloud Functions, integrating them with healthcare systems and BigQuery data warehouses.

Must Required Skills & Qualifications :

- Hands-on experience with Vertex AI (Model Registry, Pipelines, Studio) and the Gemini API.

- Proficiency in API integration and LLM orchestration tools like LangChain or the Vertex AI SDK.

- Experience with Vector Search, embeddings, and querying large datasets in BigQuery.

- 5+ years in AI/ML engineering, with at least 1 year dedicated to GenAI on Google Cloud.