GenAI Solution Architect - Hartford, CT (Onsite)

Smart Caliber Technology
Hartford, CT, United States
9 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Audit Trail Microsoft Azure BigQuery Cloud Storage Continuous Integration Data Infrastructure Data Flow Control Identity and Access Management Information Extraction
+22 more
Python (Programming Language) OpenAI Gemini Enterprise (Agent Platform) Search Technologies Model Garden (Google Cloud) Google Cloud Retrieval-Augmented Generation Multi-Agent Systems Multi-Cloud Apigee Amazon Virtual Private Cloud (VPC) Agentic-AI Vertex AI Vector Search Low Latency Machine Learning Operations Evaluation of Large Language Models Google Gemini Terraform Intelligent Document Processing Software Version Control Guidewire Agent2Agent Protocol

Job description

Own the end-to-end architecture of GenAI and agentic solutions on Google Cloud for insurance clients. You shape solutions in pre-sales, set the technical direction for delivery teams, and make sure what ships is secure, governed, scalable and cost-efficient., Define reference architectures for RAG, document intelligence and multi-agent systems on Gemini Enterprise Agent Platform (Vertex AI). Choose models (Gemini family, Model Garden, open models) based on accuracy, latency and cost; set model-routing and fallback patterns. Design agent architectures with ADK, Agent Engine, A2A and MCP; define tool, memory and session strategy. Design the data foundation: BigQuery, Cloud Storage, AlloyDB, Vector Search / Vertex AI Search, Document AI, Dataflow and Pub/Sub. Set integration patterns with policy admin, claims and underwriting systems (for example Guidewire, Duck Creek) through Apigee and event-driven APIs. Own security and compliance: VPC Service Controls, CMEK, IAM, Sensitive Data Protection, audit logging, data residency. Set up LLMOps: evaluation frameworks, prompt and model versioning, monitoring, drift and hallucination tracking, human-in-the-loop review. Lead Responsible AI reviews: explainability, bias testing, model risk documentation for insurance regulators. Estimate effort and cloud cost (tokens, compute, storage) for proposals and SOWs; build POCs that win deals. Present to client architecture boards and CXOs; mentor GenAI leads and engineers across programs.

Requirements

Deep, hands-on GCP: Gemini Enterprise Agent Platform (Vertex AI), Gemini API, Agent Builder, Cloud Run, GKE, BigQuery, Apigee, IAM and networking. Proven production RAG and agentic systems at enterprise scale. Python and solution prototyping; comfortable reviewing engineers’ code. LLM evaluation, guardrails and cost optimization (context caching, batch prediction, model tiering). Infrastructure as code (Terraform) and CI/CD for ML/GenAI. Strong stakeholder management, solutioning and documentation (ADRs, HLD/LLD). Nice to have Insurance or financial services domain: underwriting, submissions intake, claims, COI, E&S. Multi-cloud GenAI exposure (Azure OpenAI, AWS Bedrock) for comparative solutioning.

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