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AI Architect Lead

Compugra SystemsUnited States🇺🇸United StatesPosted 17 Aug 2026

Why This Role Stands Out

Lead the design and implementation of cutting-edge GenAI and agentic solutions within a reputable company, where you'll shape the future of AI governance and data stewardship. This hybrid role is perfect for experienced AI/ML architects eager to develop innovative solutions while ensuring robust privacy and explainability, offering significant opportunities for impact and career advancement.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

AI Architect Lead

Location: Rochester, Minnesota(Open for Remote).

1+Year

Platform Focus: GenAI / Agentic Google Cloud Platform


Role Description

Define and govern practical AI/agentic capabilities that augment MDM/RDM delivery and stewardship without compromising PHI/PII controls, explainability, auditability or human decision rights.

Key Responsibilities

AI use cases such as mapping recommendations, duplicate/orphan detection, match explanation, DQ anomaly detection, impact analysis and natural-language discovery.
Define AI architecture, model selection, data access, prompt/context patterns, evaluation and MDM/RDM integration.
Design human-in-the-loop controls so AI never changes authoritative master/reference data without approved governance.
Define evidence and explainability for match, mapping and DQ recommendations.
Set AI privacy/security controls for PHI/PII, access, logging, retention and data minimisation.
Define evaluation datasets, accuracy thresholds, drift monitoring and production quality controls.
Lead AI proof-of-concept and transition successful use cases into governed production services.

Primary Deliverables

AI use-case portfolio and prioritisation

AI reference architecture
AI governance / guardrail specification
Evaluation framework and benchmark results
Pilot / production integration design
AI monitoring and operating model
Required Experience & Skills

8+ years in AI/ML architecture, including enterprise generative and agentic patterns.

Strong data architecture background and integration with data workflows.
Experience deploying approved models with human-in-the-loop controls.
Good to Have


Responsible-

AI and regulated-data experience.
Vertex AI or equivalent on Google Cloud Platform.
MLOps and model monitoring.

Skills

MLOps
Google Cloud

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