Data / Gen AI Engineer Hartford, CT
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Role details
Tech stack
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Job description
We are looking for a hands-on Data Engineer / GenAI Engineer to build, test, and deploy production-ready Generative AI solutions on Google Cloud Platform (Google Cloud Platform) for insurance clients., 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
Requirements
4-8 years in software data ML engineering 1-5 years hands-on GenAI, Strong Python Fast API 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
Google Cloud Platform 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
Nice to have
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
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