Hiring nowInformation retrieval and grounding

Enterprise Search Architect

Also called Knowledge Search Architect

An Enterprise Search Architect designs search that finds the right content across an organisation while respecting who is allowed to see what. It matters because search and AI answers are only useful if they never leak restricted material.

What they do

They map the places content lives, from document stores to messaging and ticketing systems, and decide how each source is brought into an index. They work out how access rules travel with the content, so results are filtered by who is asking. They choose and combine search engines, vector indexes and rerankers. They set up evaluation sets, test relevance, and test for leaks. They work with security, IT and data owners to connect identity and entitlement systems. They also decide how often content is refreshed and what happens when permissions change.

What a strong hire delivers

In the first months, a strong hire delivers a clear architecture for the main content sources and a working path for entitlements into search. They set up a relevance and leakage test set the team trusts. They get a first set of sources indexed with access rules intact. They also leave behind a documented plan for adding further sources, handling permission changes and monitoring quality over time.

How you can tell they are good

Ask them to walk through a search system they built and how it handled permissions. Strong people explain where access rules are stored, how they are enforced at query time, and how they tested for leaks. Ask what happened when a permission changed. Worry if they treat security as a filter added at the end, or measure only relevance.

Why it is hard to fill

The title is inconsistent. Similar work appears as search engineer, knowledge architect or retrieval lead. Most candidates have deep search skill or deep security and identity skill, rarely both. Others come from application engineering and have not run relevance evaluation. Retrieval for AI answers has raised demand, so people with real permission-aware experience are scarce and often settled in their roles.

Where to find them

Look at search engineers and relevance engineers in software companies with large content collections. Information scientists and NLP engineers who moved into retrieval are another source. Application engineers who built internal search or knowledge tools for large organisations often have the entitlement experience. Enterprise software vendors, consultancies and platform teams in regulated industries are also good places to start.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for an Enterprise Search Architect

  1. Describe a search system you built across several content sources. How did you handle who could see what?

    Strong answers name the sources, where entitlements came from, and whether filtering happened at index or query time. They explain trade-offs and testing. Worry if permissions are vague, or if they only mention relevance.

  2. A document's permissions change after it has been indexed. What happens in your design?

    They should cover propagation delay, re-indexing or live checks, and caching risks. They accept some trade-off between freshness and cost. Worry if they assume permissions never change or ignore stale results.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are hiring an Enterprise Search Architect to design search across our organisation's content that returns relevant results without exposing anything a user should not see. You will work with engineering, security and data owners, and your work will underpin our AI answers as well as everyday search.

What you will do

  • Design the architecture for search across our internal content sources
  • Integrate identity and entitlement systems so results respect access rules
  • Choose and combine search engines, vector indexes and rerankers
  • Build evaluation sets for relevance and unauthorised disclosure
  • Define how content is ingested, refreshed and updated when permissions change
  • Work with content owners to improve metadata, quality and provenance
  • Document patterns so new sources can be added safely

What you will bring

  • Built and run search or retrieval systems used by real users
  • Demonstrated work enforcing access control in search or retrieval
  • Practical experience evaluating relevance with test sets and metrics
  • Comfort integrating with varied source systems and identity providers
  • Clear understanding of retrieval for generated answers
  • Able to explain trade-offs to security and product colleagues

Nice to have

  • Experience in a regulated or data-sensitive environment
  • Experience with hybrid search and reranking
  • Background in information science or NLP

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Information retrievalAdvancedRetrieve and rank relevant documents or entities
  • Retrieval-augmented generationAdvancedGround generated responses in retrieved evidence
  • Data quality and provenanceWorkingTrack dataset origin, validity and transformations
  • Model evaluationWorkingMeasure capability and failure modes credibly

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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