Hiring: Data and AI Architect Hartford, CT
Are you passionate about architecting enterprise-scale Generative AI and Agentic AI solutions? We're looking for an experienced GenAI Solutions Architect to lead the design and delivery of secure, scalable, governed, and cost-optimized AI solutions on Google Cloud. This role combines hands-on architecture, client-facing solutioning, pre-sales leadership, and technical mentorship.
Job Title: Data and AI Architect
Position Type: Long Term Contract
Location: Hartford, CT
Responsibilities:
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.
Key responsibilities
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.
Required skills
Deep, hands-on Google Cloud Platform: 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.
Gemini Enterprise (formerly Agentspace) rollout for employee-facing agents.
Model tuning and distillation; Looker semantic layer for analytics agents.
Certifications (preferred)
Google Cloud Professional Cloud Architect (required or within 3 months)
Google Cloud Professional Machine Learning Engineer
Google Cloud Generative AI Leader
Interested or open to new opportunities?
Please send your updated resume with contact details to
Thanks and Regards
Vikas Mahindrakar
New York Technology Partners
120 Wood Avenue S | Suite 504 | Iselin, NJ 08830
