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OpenAI's AI Architect team partners with organizations to turn OpenAI's most capable models into real-world impact. As a Partner Applied AI Architect, you will serve as a senior technical advisor to a portfolio of strategic partners—including global and regional system integrators, consulting firms, and technology partners—helping them build practices around OpenAI, develop solutions using OpenAI products, and take joint customers from AI opportunity through production adoption and measurable business impact.
You will own the technical strategy and architecture across partner engagements involving ChatGPT Enterprise, the OpenAI API, Codex, and agentic AI solutions. Working closely with the Revenue Partnerships team, you will translate joint business priorities into technical strategies, solution patterns, enablement plans, and a focused portfolio of high-value customer opportunities.
Key responsibilities include:
- Serve as the primary technical advisor and long-term relationship owner for a portfolio of strategic partners, building trusted relationships with their executives, AI leaders, architects, and delivery organizations.
- Develop technical strategy and plans for each partner, identifying priority solutions, use cases, technical capabilities, enablement needs, and adoption opportunities.
- Assess partners' technical capabilities and delivery readiness, identifying gaps and required investments.
- Lead technical discovery with partners and joint customers to identify and prioritize AI use cases tied to business outcomes.
- Develop clear Applied AI architectures spanning models, applications, enterprise data, integrations, identity, security, privacy, governance, evaluation, reliability, and deployment.
- Guide partners through initial and strategic OpenAI deployments, ensuring solutions meet high standards for quality, security, reliability, and responsible deployment.
- Build partner capability and technical self-sufficiency through tailored enablement, architectural guidance, solution patterns, workshops, and mentorship.
- Establish standards and mechanisms for partner-delivered solution quality, identifying risks early and intervening when necessary.
- Orchestrate OpenAI specialists across deployment, product, security, implementation, and enablement teams.
- Track partner capability, joint pipeline progress, production adoption, usage, solution quality, and measurable customer impact.
- Identify repeatable patterns across engagements and turn them into architectures, playbooks, reference solutions, and best practices.
- Bring insights from partners and customers back to Product, Engineering, Research, and Partnerships to shape product strategy and the partner ecosystem.
QUALIFICATIONS & REQUIREMENTS:
- Significant experience in senior customer- or partner-facing technical roles such as solutions architecture, partner engineering, field architecture, technical account leadership, AI deployment, or technical consulting.
- Proven success working with global or regional system integrators, consulting firms, or technology partners; understanding of how partner organizations sell, architect, and deliver complex enterprise technology.
- Experience guiding complex enterprise organizations from technical discovery and evaluation through production deployment, adoption, and measurable business impact.
- Ability to build credibility with CTOs, CIOs, CISOs, partner executives, and AI leaders while communicating effectively with architects and hands-on engineers.
- Strong software and cloud architecture foundations, including APIs, distributed systems, enterprise data, integrations, identity, security, privacy, and governance.
- Understanding of modern AI systems, frontier LLMs, agentic applications, model evaluation, retrieval, and enterprise AI workflows.
- Capability to prototype when useful, explain technical tradeoffs clearly, and work confidently with APIs, SDKs, and languages such as Python or JavaScript.
- Experience enabling technical organizations at scale, turning expertise into repeatable architectures, training, patterns, and practices.
- Understanding of enterprise security and compliance requirements and ability to guide partners and customers through technical considerations for safe AI production deployment.
- Comfort balancing the needs of OpenAI, the partner, and the end customer with sound judgment when priorities diverge.
- Ability to prioritize across a portfolio of partners and customer opportunities, focusing resources on work most likely to create durable customer value and adoption.
- Clear communication skills; ability to turn ambiguity into practical architecture, executive decisions, enablement plans, or paths to production.
- End-to-end problem ownership, quick learning, and deep commitment to helping partners and customers deploy advanced AI responsibly.
