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# GCP Data Engineer (Vertex AI)

- **Company:** Capgemini
- **Location:** Hartford, CT, United States
- **Salary:** $105,000.0 - $115,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, BigQuery, Cloud Computing, Cloud Engineering, Cloud Storage, Continuous Integration, Data Stores, Data Flow Control, Identity and Access Management, Machine Learning, Scrum Methodology, Gemini Enterprise (Agent Platform), Search Technologies, Google Cloud, Google Data Studio, Retrieval-Augmented Generation, Flask (Web Framework), Generative AI, Apigee, Build Server, Vertex AI Vector Search, Git, Fastapi, Pytest, Pgvector, Google Gemini, Restful APIs, Model Context Protocol, Terraform, Intelligent Document Processing, Looker Analytics, GPT, Docker, Agent2Agent Protocol
- **Published:** November 4, 2026
- **Apply:** https://www.capgemini.com/jobs/590202-en_US_SAPBTP/x/

## About the Role

4-8 years in software/data/ML engineering with 1-5 years hands-on GenAI experience along with Vertex AI and Google cloud platform and its services., * Strong Python FastAPI or Flask async pytest

 * Handson Gemini API Vertex AI SDK or Google Gen AI SDK
 * RAG design and at least one vector store Vector Search AlloyDB pgvector BigQuery vector search
 * LLM frameworks ADK LangChain or LangGraph
 * GCP core Cloud Run Cloud Functions Cloud Storage BigQuery IAM Secret Manager
 * REST API design Git Docker CICD
 * Good written and verbal communication with onsite and client teams, Insurance domain PC ES specialty workers comp or financial services
Document AI custom extractors OCR on scanned or handwritten forms
Agent2Agent A2A protocol or Model Context Protocol MCP tool integration
Model tuning supervised finetuning on Gemini and model monitoring
Terraform Looker or Looker Studio dashboards.

Certifications (preferred)

 * Google Cloud Professional Machine Learning Engineer
 * Google Cloud Associate Cloud Engineer or Professional Cloud Developer
 * Google Cloud Generative AI Leader good to have.

## Description

* 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 RAG pipelines chunking embeddings Vector Search Vertex AI Search grounding and citations
 * 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
 * Ship services on Cloud Run or GKE exposed through Apigee with CICD in Cloud Build
 * Move and store data with BigQuery Cloud Storage PubSub and Dataflow
 * Write evaluation sets and run quality latency and cost checks Gen AI evaluation service golden datasets
 * Apply guardrails PII masking with Sensitive Data Protection DLP safety filters IAM least privilege
 * Work in Agile sprints with QA UI and data teams write clean tested documented code.