AI Success Engineer - EDU
Post-sales technical advisor for education institutions, driving AI adoption, deployment, use case identification, and value realization with OpenAI's platform. Requires 8+ years in technical customer success or consulting roles with deep GenAI and integration expertise.
About the job
Responsibilities
- Lead the technical relationship for post-sale education customers as their trusted advisor on deployment, adoption, and value realization.
- Own account health, adoption velocity, and ongoing technical deployment and success across a portfolio of education institutions.
- Conduct technical enablement and configuration sessions across OpenAI's product portfolio.
- Identify and validate high-impact academic and administrative use cases by embedding with customer teams to understand workflows and pain points.
- Lead account-level coordination across multiple workstreams, including new product activation, change management, and customer rollout and deployment planning.
- Build strong relationships with provosts, CIOs, IT leaders, academic, and technical stakeholders; align institutional goals with OpenAI capabilities.
- Translate customer objectives into an actionable adoption roadmap with clear sequencing, milestones, and KPIs.
- Partner with Solutions Architecture, Product, Engineering, and Research by surfacing customer feedback, field patterns, and technical blockers.
- Guide value realization through student, faculty, and institutional outcomes such as engagement, research productivity, operational efficiency, and learning impact.
- Facilitate workshops for faculty, staff, and administrators on use case design, adoption best practices, champion building, and institution-wide enablement.
- Drive expansions by identifying high-leverage opportunities for new workflows.
- Serve as the technical advisor for existing customer implementations by guiding and optimizing account setup and configuration.
Requirements
- 8+ years of experience in technical customer-facing roles such as technical account management, technical GenAI consulting, solutions architecture, technical delivery leadership, or deep technical enterprise SaaS adoption work.
- Deep, hands-on knowledge of OpenAI product capabilities, APIs, SDKs, connectors, and common integration patterns.
- Ability to explain model behavior, limitations, technical tradeoffs, embeddings, retrieval augmentation, and approaches to fine-tuning or custom model usage.
- Experience translating technical concepts into clear business language and helping customers understand the strategic impact of AI technologies.
- Comfortable embedding with customers to map workflows, identify requirements, and diagnose adoption challenges.
- Excellent project and program management instincts; able to lead multi-workstream initiatives with clarity and structure.
- Enjoy being a thought partner for executive-level stakeholders while diving deep with technical teams.
- High ownership, ability to manage fast decision-making, context switching, and dynamic customer needs.
- Strong record of driving technical deployments with hands-on customer work and owning impactful adoption and value for large institutions with complex environments and multiple stakeholders.
Nice-to-Haves
- Experience working with education institutions.
Skills
Generative AI, APIs, SDKs, Embeddings, Retrieval Augmentation, Fine-Tuning, Technical Account Management, Solutions Architecture, Project Management, Change Management
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