openai - Applied AI Architect, Large Enterprise

• Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing customers and pre-sales prospects. • Partner with Account Directors on account strategy while owning the technical account plan, technical milestones, adoption priorities, and expansion opportunities. • Lead discovery with executives and technical teams to identify, qualify, and prioritize use cases tied to meaningful business outcomes. • Develop clear Applied AI Architectures spanning models, applications, data, integration, security, privacy, governance, evaluation, and deployment. • Guide customers through technical evaluations, demonstrations, workshops, prototypes, and proofs of value, securing confidence in both the solution and its path to production. • Maintain a focused use-case portfolio with clear decision criteria, ownership, blockers, success measures, delivery needs, and adoption plans. • Develop trusted relationships and technical champions across CTOs, CIOs, CISOs, AI leaders, engineering teams, and other customer stakeholders. • Qualify and coordinate support from Deployment Engineering, implementation, training and enablement, product and domain specialists, partners, and other delivery teams. • Remain accountable for technical progress and customer outcomes while ensuring delivery teams own implementation execution once engaged. • Track adoption, usage, account health, production readiness, and measurable customer impact, intervening early when risks threaten value realization. • Apply industry or digital-native expertise to recognize repeatable patterns, sharpen customer priorities, and identify relevant expansion opportunities. • Share customer insights with Product, Engineering, and Research, translating field learnings into better products, architecture guidance, and reusable practices. • Have significant experience in customer-facing technical roles such as solutions architecture, solutions engineering, technical account leadership, AI deployment, or technical customer success. • Have guided enterprise organizations from technical evaluation through production adoption and measurable business impact. • Build credibility with senior technical and business leaders while communicating equally well with hands-on engineers. • Bring strong software and cloud architecture foundations, including APIs, distributed systems, data integration, identity, security, and privacy. • Understand modern AI systems, frontier LLM models, agentic applications, model evaluation, retrieval, or enterprise AI workflows. • Can prototype, explain technical tradeoffs, and work confidently with APIs, SDKs, and languages such as Python or JavaScript. • Exercise sound judgment about when to go deep personally, when to involve specialists, and how to define clear handoffs and ownership. • Have experience developing technical account plans, prioritizing complex customer portfolios, and connecting adoption to measurable outcomes. • Bring meaningful expertise in a relevant industry or strong fluency with the needs of digital-native businesses. • Communicate clearly and can turn ambiguity into a practical technical narrative, executive decision, or action plan. • Work collaboratively across disciplines and care deeply about helping organizations deploy advanced AI responsibly.