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About the role
You are being hired as a Data Scientist with expertise in Generative AI and Google Cloud Platform (GCP) to develop AI-powered automation solutions for health claims processing systems. Your main responsibilities will include designing and implementing production-grade GenAI applications using Google Cloud Vertex AI and Gemini. This will involve processing unstructured medical documents to enhance claim validation accuracy and adjudication turnaround time. Key Responsibilities: - Build and deploy AI agents using Gemini (Pro/Flash) and Vertex AI Agent Builder - Develop Retrieval-Augmented Generation (RAG) pipelines - Implement Vector Search and embedding-based retrieval - Utilize Document AI / Vision AI for medical document parsing (OCR + structured extraction) - Conduct prompt engineering, model evaluation, and fine-tuning - Deploy scalable AI microservices using Cloud Run / GKE / Cloud Functions - Integrate AI APIs with healthcare systems and BigQuery - Optimize performance, latency, and monitoring of GenAI workflows Qualifications Required: - 5-7 years of experience in Data Science / Machine Learning - Minimum 1 year of hands-on experience in Generative AI on GCP - Strong proficiency in Vertex AI (Pipelines, Model Registry, Studio), Gemini API, Vertex AI SDK, and LangChain or similar LLM orchestration framework - Familiarity with Embeddings and Vector Databases, RAG architecture, BigQuery, API development, and deployment - Strong Python programming skills The company is looking for candidates who have exposure to the Healthcare / Insurance domain, experience with compliance-driven AI systems, and managing large-scale production ML systems. You are being hired as a Data Scientist with expertise in Generative AI and Google Cloud Platform (GCP) to develop AI-powered automation solutions for health claims processing systems. Your main responsibilities will include designing and implementing production-grade GenAI applications using Google Cloud Vertex AI and Gemini. This will involve processing unstructured medical documents to enhance claim validation accuracy and adjudication turnaround time. Key Responsibilities: - Build and deploy AI agents using Gemini (Pro/Flash) and Vertex AI Agent Builder - Develop Retrieval-Augmented Generation (RAG) pipelines - Implement Vector Search and embedding-based retrieval - Utilize Document AI / Vision AI for medical document parsing (OCR + structured extraction) - Conduct prompt engineering, model evaluation, and fine-tuning - Deploy scalable AI microservices using Cloud Run / GKE / Cloud Functions - Integrate AI APIs with healthcare systems and BigQuery - Optimize performance, latency, and monitoring of GenAI workflows Qualifications Required: - 5-7 years of experience in Data Science / Machine Learning - Minimum 1 year of hands-on experience in Generative AI on GCP - Strong proficiency in Vertex AI (Pipelines, Model Registry, Studio), Gemini API, Vertex AI SDK, and LangChain or similar LLM orchestration framework - Familiarity with Embeddings and Vector Databases, RAG architecture, BigQuery, API development, and deployment - Strong Python programming skills The company is looking for candidates who have exposure to the Healthcare / Insurance domain, experience with compliance-driven AI systems, and managing large-scale production ML systems.