EmergingInformation retrieval and grounding

Grounding Evaluation Specialist

Also called Answer Grounding Analyst

A Grounding Evaluation Specialist tests whether an AI system's claims actually follow from the evidence it was given. They make unsupported answers visible before customers find them, which protects trust in any product built on retrieval.

What they do

They take generated answers and the passages behind them, then break each answer into individual claims. For every claim they judge whether the evidence supports it, contradicts it or says nothing. They check that each citation points to the passage that carries the claim. They write the rubric that defines these judgements, run it on samples, resolve disagreements between reviewers and keep the adjudicated set clean. They then look at failure patterns and trace them back to retrieval, ranking, prompting or the model. Much of this work sits inside search, NLP or application engineering jobs today.

What a strong hire delivers

In the first months, a strong hire gives the team a written claim-support rubric that reviewers apply consistently. They build an adjudicated evaluation set that the team trusts and can rerun. They set up measures for unsupported-claim detection and citation correctness. They also hand engineers a clear account of where answers go wrong and which part of the pipeline causes it.

How you can tell they are good

Ask them to take a short answer and a few passages and mark which claims are supported. Good candidates split claims carefully, spot partial support and notice when a citation is real but irrelevant. Ask how they would measure agreement between reviewers and what they do when it is low. Be wary of anyone who treats fluent answers as correct or relies on a single score.

Why it is hard to fill

Almost nobody has this title. The work hides inside search relevance, NLP research, information science and application engineering roles. Candidates tend to be strong on one side: either judging text carefully or building retrieval systems. You need both, plus patience for rubric writing. Titles such as Answer Grounding Analyst appear rarely, so job title searches miss most of the real talent.

Where to find them

Look at search relevance and quality teams, NLP and applied research groups, and information science backgrounds such as librarianship, knowledge management and enterprise search. Application engineers who have built retrieval-augmented products and had to debug bad answers are another source. Companies shipping question answering, research assistants, legal or support tools, and enterprise search often have someone doing this quietly under another title.

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 a Grounding Evaluation Specialist

  1. Describe a time you judged whether an answer was supported by its sources. How did you define supported?

    A strong answer gives a concrete definition, covers partial support and contradiction, and explains how edge cases were settled. Worry if they only describe gut feel or say they checked that answers sounded right.

  2. How would you break a long generated answer into claims for evaluation?

    Good answers describe splitting into atomic, checkable statements while keeping context such as qualifiers and references. They mention the cost of over-splitting. Worry if they treat each sentence as one claim without thought.

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

Job description you can post

We are building products that answer questions from evidence, and we need to know when those answers can be trusted. We are looking for a Grounding Evaluation Specialist to define what supported means, measure it, and help the team fix what the measurements reveal.

What you will do

  • Write and maintain a claim-support rubric with clear examples
  • Break generated answers into claims and judge them against the supplied evidence
  • Check that citations point to the passages that support each claim
  • Build and adjudicate an evaluation set the team can rerun
  • Track unsupported-claim detection and citation correctness over time
  • Trace failure patterns to retrieval, ranking, prompting or model behaviour
  • Report findings to engineers and product owners in plain terms

What you will bring

  • Demonstrated work judging whether text is supported by evidence
  • Experience with information retrieval or search quality evaluation
  • Clear written style, shown in rubrics, guidelines or analysis
  • Comfort measuring reviewer agreement and resolving disagreements
  • Working knowledge of retrieval-augmented generation systems
  • Attention to data quality and source provenance

Nice to have

  • Experience with rerankers or vector indexes
  • Background in information science, NLP or search relevance
  • Experience building evaluation tooling

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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