TL;DR

Senior AI Architect (AI Engineering): Lead design, development, and governance of advanced AI solutions including LLMs and MLOps on Google Cloud Platform with an accent on AI governance, security, and production-grade deployment. Focus on designing agentic architectures, Retrieval Augmented Generation pipelines, and ensuring compliance with AI Risk Board standards.

Location: Hartford, Connecticut, United States

Salary: $129,000 - $160,000 USD

Company

%hirify_global% is a global technology services company specializing in digital engineering and IT consulting.

What you will do

Lead end-to-end AI development, balancing hands-on model design with mentoring AI teams.
Design, build, and deploy production-grade machine learning models including LLMs on Google Cloud Platform Vertex AI.
Manage collaboration with internal AI teams, Google, and technology vendors to drive innovation and align with best practices.
Own AI governance processes including AI Risk Board reviews, data security, compliance, and ethical AI considerations.
Design and evaluate Conversational AI models leveraging Google CCAI CES components and robust evaluation frameworks.
Optimize models for performance, scalability, and accuracy in production environments.

Requirements

Location: Must be based in Hartford, Connecticut, United States
Advanced hands-on experience in Machine Learning, LLMs, and MLOps.
Proven expertise in Google Vertex AI, Python, and Google CCAI CES platforms.
Deep understanding of AI governance, AI Risk Board compliance, security, and responsible AI principles.
Experience with model evaluation frameworks, agentic architectures, and Retrieval Augmented Generation pipelines.
Strong communication and collaboration skills for cross-functional teams and vendor engagement.

Nice to have

Experience with Parameter Efficient Fine Tuning (PEFT).

Culture & Benefits

Work in a leading global technology services company focused on innovation.
Opportunity to collaborate with top AI teams and technology vendors like Google.
Focus on balancing innovation with operational rigor in production-grade AI environments.