GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #16
A Generative AI Engineer is building a Generative AI system that suggests the best matched employee team member to newly scoped projects. The team member is selected from a very large team. The…
The correct answer is D. Create a tool for finding available team members given project dates. Embed team profiles into a. Option D is correct because it uses a two-stage hybrid retrieval architecture: a structured tool filters candidates by date availability (a hard constraint best handled by traditional logic or a database query), and then a vector store with embedded employee profiles performs…
Question
A Generative AI Engineer is building a Generative AI system that suggests the best matched employee team member to newly scoped projects. The team member is selected from a very large team. The match should be based upon project date availability and how well their employee profile matches the project scope. Both the employee profile and project scope are unstructured text. How should the Generative AI Engineer architect their system?
Options
- ACreate a tool for finding available team members given project dates. Embed all project scopes
- BCreate a tool for finding team member availability given project dates, and another tool that uses
- CCreate a tool to find available team members given project dates. Create a second tool that can
- DCreate a tool for finding available team members given project dates. Embed team profiles into a
How the community answered
(48 responses)- A13% (6)
- B6% (3)
- C4% (2)
- D77% (37)
Explanation
Option D is correct because it uses a two-stage hybrid retrieval architecture: a structured tool filters candidates by date availability (a hard constraint best handled by traditional logic or a database query), and then a vector store with embedded employee profiles performs semantic similarity search to find the best profile match against the project scope (an unstructured text matching problem). This separates concerns cleanly - availability is a boolean filter, profile matching is a semantic search. Options A and B have incomplete or incorrectly described tooling. Option C is similarly close but option D most clearly describes embedding profiles into a vector store for semantic matching after the availability filter.
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