AI Development Architect

Job Summary

The AI Development Architect leads the development and integration of AI capabilities across Sentinel U's product portfolio. This role ensures initiatives are scalable, practical, and aligned with business objectives and user needs. As the company builds its AI capability from the ground up, the Architect defines AI application strategies, makes foundational technical decisions, and translates emerging AI capabilities into scalable solutions for simulation and learning platforms. The role combines architectural leadership with hands-on development.

Distance Learning

• Design, build, and deploy AI-enabled systems (LLMs, voice AI, vector databases)
• Maintain integrations
• Build data pipelines for interaction data capture
• Ensure scalability and performance

Data Architecture

• Design data models
• Implement ETL processes for large-scale learner data
• Manage cloud-based infrastructure (Azure preferred)

Strategy & Enablement

• Partner with Product leadership to identify high-impact AI use cases
• Evaluate tools/frameworks for build vs. buy decisions
• Define AI-powered user experiences

Success Measures (Year One)

• Successful integration of AI capabilities into core projects with measurable user adoption
• AI-driven features demonstrate improvements in workflow efficiency and learner outcomes
• Reliable data pipelines supporting analytics and future modeling
• Maintained and improved AI system performance (accuracy, consistency)

Qualifications

• Minimum Requirements: 5+ years of experience in software development or data engineering; 2–3+ years of recent experience with modern AI technologies (LLMs, embeddings, etc.); Hands-on experience building and deploying AI systems in production; Strong proficiency in database design (T-SQL) and Python/C# coding; Experience with cloud platforms (Azure preferred: Data Factory, Data Lake, Databricks); Familiarity with third-party AI services (OpenAI, voice platforms); Bachelor's degree in Computer Science, Information Systems, or equivalent experience.
• Preferred Qualifications: Experience in EdTech, healthcare, or simulation-based products; Exposure to agent-based systems and orchestration frameworks; Microsoft Certified: Azure AI Engineer Associate (AI-102) or similar certification; Proven success in scaling product delivery practices.