- Partner with Product Management and relevant stakeholders to evaluate and prioritize AI opportunities that address customer and organizational needs, contributing technical judgment about feasibility, risk, and whether AI is the appropriate approach.
- Lead the technical design, prototyping, implementation, deployment, and operation of secure, reliable, and scalable AI-enabled products and internal tools.
- Translate Teachstone’s responsible AI principles and policies into system requirements and engineering practices, including appropriate evaluation, data protection, risk mitigation, monitoring, and human oversight.
- Establish reusable architectures, implementation patterns, tools, and documentation that enable Teachstone to develop and maintain AI-enabled systems sustainably.
- Guide choices among models, platforms, vendors, and build-versus-buy options by balancing customer and staff needs with quality, cost, risk, performance, maintainability, and governance requirements.
- Define measures of success and use production data, evaluations, and stakeholder feedback to improve the quality, effectiveness, and efficiency of AI-enabled systems over time.
- Contribute to Engineering’s effective and responsible use of AI-assisted development tools by sharing practical patterns, lessons learned, and guidance with peers.
People and partnership development
Build AI literacy across Teachstone by mentoring others and helping cross-functional partners understand AI’s capabilities, limitations, effective uses, and situations in which other approaches are better suited.
Stewardship and organizational impact
Guide teams toward approved and preferred AI services, helping Teachstone adopt AI consistently, securely, responsibly, and in alignment with organizational priorities.