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Director, Domain Context Management at Gap Inc.
Lead the development of governed business knowledge that helps AI agents work across a defined enterprise domain. Translate expert processes and decisions into structured context in partnership with business and technology teams.
विवरण
- Develop structured business context for AI agents across an enterprise domain.
- Document business processes with business teams and technology partners.
- Turn expert judgment, decision logic, and exceptions into governed, reusable context.
- Own the quality, completeness, and readiness of domain context for AI agents.
- Work with the Director of Agentic Pipeline Management to meet stage-gate standards.
- Gather tacit knowledge, business rules, trade-offs, and exceptions through interviews, workshops, and observation.
- Create reusable context through process maps, decision frameworks, business rules, examples, and edge cases.
- Maintain the domain’s business context library and knowledge architecture.
- Manage context governance and its lifecycle, including ownership, approvals, versioning, reviews, and retirement of outdated or conflicting material.
- Partner with Product Management, Data Science, and Engineering to define agent requirements and evaluation scenarios from business context.
- Improve context using evaluation results and production feedback.
- Reconcile conflicting expert input and surface context-readiness risks early.
आवश्यकताएँ
- Understand end-to-end business processes in a relevant domain such as design, product development, or sourcing, with demonstrated business operator experience.
- Show the ability to break down complex processes and expert decisions and document them clearly in process maps, requirements, or decision frameworks.
- Bring strong systems thinking.
- Have strong facilitation and interviewing skills.
- Establish credibility with Designers, Technical Designers, Product Development, and Sourcing partners.
- Challenge respectfully and resolve conflicting input.
- Have working familiarity with AI agents, large language models, context engineering, retrieval, and evaluation.
- Demonstrate effective partnership across Business, Product Management, Data Science, and Engineering.
- Create structure, standards, and reusable systems in ambiguous environments.
- Communicate clearly in writing.
- Retail or apparel industry experience is a plus.
- Experience with sourcing and product development systems, such as PLM, and related data is a plus.
- Experience with governance, taxonomy, or knowledge architecture is a plus.
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