GenAI Engineer — Vertex AI on GCP for Insurance

Capgemini; New York (NY); Hybrid; USD 105,000 - 115,000; Full time

Benefits offered by this job

Paid time off

Medical, dental, vision insurance

Retirement plan (401(k)

Life and disability insurance

Employee assistance program

Job summary

Capgemini seeks a GenAI engineer to build, test and deploy production GenAI solutions on Google Cloud for insurance clients. You will turn architecture into code, owning features from prototype to production, and collaborate with QA, UI and data teams in agile sprints.

You will design prompts, build RAG pipelines, deploy agents with the ADK, and ensure data handling with DLP and safety guardrails, while leveraging Gemini/Vertex AI across the stack.

Qualifications

• Experience building GenAI solutions on Google Cloud for insurance clients.
• Design and tune prompts, structured outputs and function calling for insurance documents.
• Build RAG pipelines: chunking, embeddings, Vector Search / Vertex AI Search, grounding and citations.
• Ship services on Cloud Run or GKE with CI/CD in Cloud Build.

Responsibilities

• Build GenAI applications with Gemini models on Gemini Enterprise Agent Platform (Vertex AI).
• Design and tune prompts, structured outputs and function calling for insurance documents (submissions, ACORD forms, COIs, loss runs, policies).
• Build agents with the Agent Development Kit (ADK) and deploy them on Agent Engine; integrate tools and APIs.
• Extract and classify documents with Document AI and Gemini multimodal input.
• Move and store data with BigQuery, Cloud Storage, Pub/Sub and Dataflow.

Skills

Strong Python

REST API design

Git

CI/CD

LangChain

LangGraph

ADK

Tools

Gemini API / Vertex AI SDK

LangChain or LangGraph

Vector store (Vector Search)

Agent Development Kit (ADK)

Cloud Run / GKE

Job description

Capgemini seeks a GenAI engineer to build, test and deploy production GenAI solutions on Google Cloud for insurance clients. You will turn architecture into code, owning features from prototype to production, and collaborate with QA, UI and data teams in agile sprints.

You will design prompts, build RAG pipelines, deploy agents with the ADK, and ensure data handling with DLP and safety guardrails, while leveraging Gemini/Vertex AI across the stack.