Applied AI Architect, Education

Responsibilities

• Serve as the primary technical advisor and long-term technical relationship owner for a portfolio of education customers and prospects.
• Partner with Account Directors on account strategy while owning technical account plans, milestones, adoption priorities, value realization, and expansion opportunities.
• Lead discovery with executives, academic leaders, researchers, faculty, administrators, and technical teams to identify and prioritize institutional AI use cases.
• Design applied AI architectures spanning models, applications, institutional data, identity, integrations, security, privacy, governance, evaluation, and deployment.
• Lead technical evaluations, demonstrations, workshops, prototypes, and proofs of value.
• Create adoption roadmaps with workstreams, sequencing, milestones, stakeholder ownership, governance, risks, success measures, and change-management requirements.
• Develop use-case portfolios across teaching and learning, research, student and faculty services, knowledge management, software development, and administrative operations.
• Build trusted relationships and technical champions across CIOs, CTOs, CISOs, provosts, deans, research leaders, faculty, and administrators.
• Coordinate support from deployment engineering, implementation, training, enablement, product, research, education specialists, partners, and delivery teams.
• Track adoption, usage, account health, production readiness, and measurable customer impact; intervene when risks threaten value realization.
• Identify repeatable education patterns and reusable architectures for responsible adoption.
• Translate field insights into feedback for Product, Engineering, and Research.
• Identify expansion opportunities across academic, research, administrative, and operational workflows.

Requirements

• Significant experience in customer-facing technical roles such as solutions architecture, solutions engineering, technical account leadership, AI deployment, or technical customer success.
• Experience guiding complex organizations from technical evaluation through production adoption and measurable value realization.
• Strong software and cloud architecture foundations, including APIs, distributed systems, data integration, identity, security, and privacy.
• Understanding of modern AI systems, frontier large language models, agentic applications, model evaluation, retrieval, or enterprise AI workflows.
• Ability to prototype and communicate technical tradeoffs using APIs, SDKs, and languages such as Python or JavaScript.
• Experience developing technical account plans, prioritizing complex customer portfolios, and connecting adoption to measurable outcomes.
• Ability to translate technical capabilities into institutional value across student success, research productivity, faculty enablement, administrative effectiveness, accessibility, risk, and governance.
• Strong executive, technical, and cross-functional communication skills.
• Ability to deploy advanced AI safely and responsibly in complex, mission-driven environments.

Nice-to-haves

• Meaningful experience with education technology, higher education, K–12 systems, research institutions, or similarly consensus-oriented environments.
• Experience with education-sector governance, accessibility, data privacy, change management, or responsible AI adoption.