Hiring nowResponsible AI governance and risk

AI Ethicist

Also called Applied AI Ethics Lead

An AI Ethicist advises on the value trade-offs inside product and deployment decisions. They help a company decide what it should build and ship, and how to defend those choices to users, regulators and its own staff.

What they do

They sit alongside product, engineering, legal and risk teams and review what is being built and where it will be used. They run fairness and impact assessments, write down the trade-offs, and recommend what to change, limit or stop. They draft guidance for teams, take part in launch reviews and escalate hard cases to senior leaders. They also explain technical risks in plain language to people who must make the final call. Much of the job is being in the room early, before a decision is locked in.

What a strong hire delivers

In the first months a strong hire gives the company a clear way to raise and decide ethical questions. Teams know when to ask for review and who owns the answer. Expect a working impact assessment process, a record of decisions and their reasoning, and at least a few launches that changed for the better because they were involved early.

How you can tell they are good

Ask them to walk through a real decision where values pulled in different directions. Listen for what they recommended, what they gave up, and who disagreed. Strong people name specific harms, use evidence, and accept that some trade-offs have no clean answer. Ask them to explain a technical risk to a non-technical executive. Be wary of abstract theory with no shipped outcome.

Why it is hard to fill

The title is used loosely, so CVs vary a great deal. Some candidates are philosophers with little product exposure. Others are compliance or risk people who have never handled real ethical judgement. The useful hire needs both, and that mix is uncommon. Many strong people also sit under other titles, so searching by title alone misses them. Labs and large enterprises compete for the same small group.

Where to find them

Look in risk management, compliance, internal audit and technology governance teams, especially where AI is already in use. Responsible AI teams at frontier labs and large enterprises are another source. Philosophy and ethics graduates who moved into product or policy work can be excellent if they have shipped alongside engineers. Check for people titled policy, trust, or governance lead.

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 AI Ethicist

  1. Describe a product decision where you advised on a values trade-off. What did you recommend and what happened?

    A strong answer names a real decision, the options, the harms weighed and the outcome, including where they were overruled. Worry if the story is hypothetical, vague about impact, or claims everyone simply agreed with them.

  2. How do you decide whether a feature needs a fairness or impact assessment, and how deep to go?

    Good answers use risk tiers based on users affected, severity, reversibility and context of use. They scale effort to risk. Worry about a one-size process that slows everything, or no clear criteria at all.

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

Job description you can post

We are hiring an AI Ethicist to help us make sound decisions about what we build and how it is used. You will work with product, engineering, legal and risk teams, giving clear advice on difficult trade-offs before products reach users.

What you will do

  • Advise product and engineering teams on value trade-offs in design and deployment decisions
  • Run fairness and impact assessments and act on the findings
  • Take part in launch reviews and escalate unresolved concerns
  • Write practical guidance and decision records teams can follow
  • Work with legal, risk and assurance colleagues on AI governance
  • Explain technical risks clearly to senior leaders and non-technical staff

What you will bring

  • Examples of advising on real product or deployment decisions involving AI
  • Demonstrated work in risk management, governance, audit or responsible AI
  • Experience carrying out fairness or impact assessments
  • Able to explain technical issues clearly to varied audiences
  • Sound product understanding and comfort working with engineers
  • Good judgement under disagreement, with clear written reasoning

Nice to have

  • Background in philosophy or applied ethics
  • Experience preparing for regulatory or customer scrutiny
  • Experience building an AI governance process from scratch

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

Skills that matter

  • AI risk managementWorkingIdentify, assess, treat and monitor AI risks
  • AI governance and assuranceWorkingAssign accountability and verify lifecycle controls
  • Fairness and impact assessmentWorkingAssess unequal errors, access and downstream impacts
  • 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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