Hiring nowAI solution delivery, consulting and architecture

Vertical AI Specialist

Also called Vertical AI Specialist (Legal/Health/Finance) · Domain AI Engineer

A Vertical AI Specialist is a domain expert who configures and validates AI for a regulated field such as law, health or finance. They make the product trustworthy enough for customers who cannot afford to be wrong.

What they do

They sit between the domain and the technology. They take a real workflow, such as contract review, clinical triage or credit assessment, and work out how AI should handle it. They configure prompts, retrieval and tool connections, then test outputs against what a qualified practitioner would accept. They write the acceptance criteria, flag where the system should refuse or escalate, and document known limits. They join customer calls, explain behaviour in the customer's language, and take what they hear back to engineering. They also keep track of regulatory expectations and shape how risk is managed.

What a strong hire delivers

In the first months, a strong hire turns a vague domain need into a tested, documented configuration that customers will sign off. They build a validation set drawn from real practice and agree clear pass marks with the team. They reduce back and forth between sales, engineering and customers. They also leave a risk log that shows what the system can and cannot be trusted to do.

How you can tell they are good

Ask them to walk through a system they validated in a regulated setting. Listen for how they defined correct, who judged it, and what they did when the model was fluent but wrong. Ask them to explain a technical limit to a sceptical practitioner. Strong people are specific about failure and comfortable saying where AI should not be used.

Why it is hard to fill

Very few people hold a serious domain credential and also have hands-on technical fluency. Titles vary widely, so searching by job title misses most of them. Candidates often sit in consulting, delivery or practice roles and do not see themselves as AI people. Vertical AI startups compete for the same small group, so speed and a clear remit matter.

Where to find them

Look first at solution architects, consultants, systems integrators and technical delivery leads who have worked inside one regulated sector. Also look at lawyers, clinicians and finance professionals who moved into legal technology, health technology or financial technology product work. Vertical AI startups, sector software vendors and specialist advisory teams are the main sources.

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 Vertical AI Specialist

  1. Describe a time you validated an AI or automated system in a regulated setting. How did you decide it was good enough?

    Strong answers define acceptance criteria, name who reviewed outputs and show a real test set. They admit trade-offs and residual risk. Worry if the answer rests on demos, general impressions or the vendor's own claims.

  2. How would you build a test set for a contract review or clinical summary feature?

    Look for real samples, edge cases, expert review, agreed scoring and a plan to refresh it. They should mention privacy and consent. Worry if they only suggest a handful of cherry-picked examples.

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

Job description you can post

We build AI for a regulated field, and our customers need to trust what it does. We are looking for a domain expert with strong technical fluency to configure, test and explain our product. You will work with engineering, sales and customers to make it safe and useful in real practice.

What you will do

  • Turn customer workflows into clear AI configurations and acceptance criteria
  • Build and maintain validation sets reviewed by qualified practitioners
  • Configure prompts, retrieval and tool integrations for the domain
  • Identify failure modes and define when the system should refuse or escalate
  • Maintain a risk log and documentation for customers and auditors
  • Join customer and sales conversations to explain behaviour and limits
  • Feed domain insight back to product and engineering

What you will bring

  • Demonstrated work in one regulated sector such as legal, health or finance
  • Recognised domain credential or equivalent practical standing
  • Hands-on experience validating or integrating automated or AI systems
  • Clear written and spoken technical communication for non-technical experts
  • Sound judgement on risk, escalation and human review
  • Experience in delivery, consulting or solution architecture

Nice to have

  • Experience with agent frameworks and tool integrations
  • Familiarity with sector regulation and audit expectations
  • Experience supporting pre-sales technical conversations

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

Skills that matter

  • Sales and solution architectureWorkingMatch technical solutions to validated customer needs
  • Tool and protocol integrationWorkingConnect models to external data and capabilities
  • AI risk managementWorkingIdentify, assess, treat and monitor AI risks
  • Technical communicationWorkingExplain evidence and limitations to relevant readers

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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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