OpenAI Certification Architect defines the framework and standards for OpenAI certifications to verify AI competence. This senior role involves building reusable assessment architectures and collaborating with cross-functional teams.
Responsibilities
As Certification Architect, you will define the framework, standards, and assessment architecture that make OpenAI certifications a trusted signal of demonstrated capability.
This is a senior hands-on role on the Certification team that will build reusable foundations for a growing portfolio: clear competency standards, defensible assessments, scalable in-product delivery, and evidence of continued competence.
We’re looking for someone who combines deep certification and assessment expertise with the ability to innovate new and meaningful ways to demonstrate practical AI competence. You will work closely with certification specialists, technical subject matter experts, learning product and engineering teams, operations and policy partners, and stakeholders across the go-to-market organization.
The program is early, and you will help shape how people demonstrate capability in ChatGPT and Codex. Success means building standards that are rigorous, usable, and adaptable as AI technology and professional roles evolve.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
Own the credential framework and shared competency standards, distinguishing completed learning, demonstrated skills, and formal certification, with clear capability claims and evidence requirements for each.
Establish reusable assessment standards and guidance for certification pods across job-task analysis, competency models, assessment blueprints, performance tasks, scoring rubrics, and passing standards.
Own the validation approach and evidence documentation requirements. Partner with pod leaders to validate certification proposals against job relevance, representative task coverage, scoring consistency, fairness, and appropriate interpretation of results.
Define exam delivery architecture and requirements with product, engineering, operations, and third parties, spanning registration, identity verification, monitoring, permitted assistance, evidence capture, scoring, human review, appeals, customer support, and record management.
Define expectations for continued competence validation post-assessment.
Partner with learning, operations, policy, legal, privacy, security, and accessibility teams to align preparation with competencies while protecting assessment integrity and establishing appropriate evidence access, retention, accommodations, and review processes.
