Principal Cloud AI Architect

About the job

We are seeking a hands-on AI Architect to design and implement intelligent enrollment systems that leverage large language models, distributed agents, and enterprise data platforms to improve student engagement and enrollment conversion. This role will lead the architecture of a decision intelligence platform that analyzes student application data, generates AI-driven insights, and recommends next-best actions for enrollment specialists. The platform integrates Google Cloud AI services, Salesforce data, and multi-agent orchestration frameworks to deliver scalable AI capabilities across the enrollment lifecycle. Key Responsibilities AI System Architecture Design scalable AI architectures using Google Cloud services including: • BigQuery • Vertex AI - Gemini models • Cloud Run • Cloud Functions Architect distributed AI systems capable of orchestrating multiple services and agents to process student data and generate insights. LLM & Generative AI Systems Design and implement LLM-powered workflows including: • AI-generated enrollment insights • application and transcript summarization • next-best-action recommendations • AI-assisted outreach messaging Develop prompt engineering frameworks and structured output systems to ensure reliable AI responses. Multi-Agent Orchestration Design architectures that coordinate specialized AI agents responsible for: • data retrieval • student risk assessment • AI insight generation • recommendation systems Implement orchestration patterns using containerized microservices and REST APIs. Data & Analytics Integration Leverage enterprise data sources including: • Salesforce CRM • BigQuery datasets • enrollment activity logs • application and transcript data Design efficient data retrieval pipelines that feed AI services with relevant context. Enterprise Integration Integrate AI systems with enterprise applications including: • Salesforce Lightning • enrollment specialist dashboards • internal analytics tools Ensure AI services can be embedded within existing workflows. Governance & Reliability Ensure production-ready AI systems by implementing: • monitoring and logging • prompt reliability safeguards • feedback loops for AI output improvement • responsible AI practices

Requirements

• Google Cloud
• Python
• Node.js

Qualifications

• 8+ years experience in cloud architecture
• Strong experience with Google Cloud Platform

Preferred Technologies

• Google Cloud
• Python
• Node.js