Data and knowledge

Information retrieval and grounding

Information retrieval and grounding is the work of finding relevant evidence and tying generated answers back to it. AI companies need it because a fluent answer is not a trustworthy one, and users want to see what a claim rests on.

More teams are putting models in front of real company content, and fluent answers that cannot be traced to a source cause trouble fast. Demand is forming around retrieval quality, permissions and evidence checks. The hires are tricky because the skills sit across search, language modelling and application engineering. Strong candidates judge answer support separately from how well an answer reads. Few people have done that at scale.

Hiring now 3Emerging 1

Roles in this family

4 roles

Hiring nowRetrieval-Augmented Generation EngineerA RAG engineer builds the service that finds the right evidence and makes generated answers stick to it. It matters because users trust answers only…Hiring nowSearch Relevance EngineerA Search Relevance Engineer improves how well a system finds the right evidence for the queries that matter. Better retrieval means grounded…Hiring nowEnterprise Search ArchitectAn Enterprise Search Architect designs search that finds the right content across an organisation while respecting who is allowed to see what. It…EmergingGrounding Evaluation SpecialistA Grounding Evaluation Specialist tests whether an AI system's claims actually follow from the evidence it was given. They make unsupported answers…

Where the people come from

Search, NLP, information science or application engineering

Not to be confused with. Answer support must be evaluated independently of fluency.

Core skills

  • Information retrieval
  • Data quality and provenance
  • Model evaluation
  • Retrieval-augmented generation

Where it is used

  • Enterprise software and developer tools
  • Legal services and intellectual property
  • Media journalism and publishing
  • Customer service and contact centres

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