Enterprise Context Architect
$129,200–$174,800 year
Remote
Job Summary
Define the source-of-truth strategy for enterprise knowledge by assessing authoritative systems, indexing structures, and AI eligibility criteria. Establish enterprise standards for content structure, metadata, and provenance while designing control models for AI actions, including eligibility rules and escalation paths. Lead platform and connector strategy across the content stack, partnering with IT and Engineering on architecture and access grants. Build a federated operating model where domain experts maintain accuracy within shared standards and lifecycle policies. Define content quality through retrieval and grounding evaluations for priority use cases. Co-own criteria for AI content eligibility and permissions modeling with Legal, Privacy, and Security. This is the first role of its kind at Dropbox, focusing on the knowledge layer that connects content, context, and action for AI systems.
Required Qualifications
- 7+ years designing how information is structured, owned, and maintained at enterprise scale
- at least 2 years applying that work to AI retrieval and grounding
- Direct experience preparing content for AI consumption
- working fluency in retrieval-augmented generation
- working fluency in grounding
- working fluency in semantic chunking
- working fluency in embeddings
- working fluency in vector search
- working fluency in citations
- Hands-on experience with knowledge graphs
- Hands-on experience with ontologies
- Hands-on experience with semantic models
- Track record building federated operating models across functions outside direct reporting lines
- evidence of metadata standards or authoring frameworks adopted at scale
- Demonstrated ability to influence senior stakeholders across Engineering, IT, Legal, Security, and business functions
- Sound judgment on balancing central standards with domain expertise
Desired Qualifications
- Hands-on experience with enterprise platforms such as ServiceNow, Atlassian, Microsoft 365 or Copilot Search, Slack, or Notion
- Familiarity with structured authoring (such as DITA)
- Familiarity with controlled vocabularies
- Familiarity with knowledge operations methodologies such as KCS
- Experience with AI evaluation tooling and frameworks for measuring retrieval quality, groundedness, and answer relevance
- Background working in regulated, policy-heavy, or high-risk content domains
- Working knowledge of NIST AI RMF
- Working knowledge of OWASP GenAI guidance
- Working knowledge of comparable risk frameworks
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