Hiring nowSynthetic data and environment generation

Simulation Scenario Designer

Also called AI Scenario Engineer

A Simulation Scenario Designer builds the realistic test scenarios and edge cases that show where an AI system breaks. They matter because a team can only fix the failures it has thought to test for.

What they do

They work out which conditions matter for the system under test, then build scenarios to cover them. That means reading failure reports, talking to product and safety colleagues, and turning vague worries into specific cases. They use generative models and simulators to produce examples, then run dataset validators to check the examples are realistic and not duplicates. They tag each scenario by condition and known failure mode, and keep a coverage map that shows what is tested and what is not. Scenarios are versioned, so results can be compared from one release to the next. They also check that synthetic cases do not leak private data.

What a strong hire delivers

In the first months, a strong hire gives the team a versioned scenario library that people actually run. They produce a coverage map that shows which important conditions and known failure modes are tested and where the gaps sit. They agree a short list of priority gaps with engineering and safety, then close the worst ones. Evaluation results become easier to trust and to compare between releases.

How you can tell they are good

Ask them to walk through a scenario library they built. A good candidate explains how they chose the conditions, how they knew coverage was adequate, and how they checked that the scenarios were realistic. Ask what they would cut if time ran short. Strong people talk about failure modes and gaps. Weak ones talk about volume of examples.

Why it is hard to fill

The title is not settled. The same work appears as scenario engineer, simulation engineer, test engineer or evaluation specialist, so keyword searches miss people. Candidates tend to be strong in one strand, such as simulation or statistics, and thin in the others. Few have combined generative modelling with disciplined test design. Founders often ask for all of it, and the pool is small.

Where to find them

Look at test and verification engineers, simulation engineers and people who work with digital twins. Statisticians with experimental design experience move across well. So do generative modelling researchers who care about evaluation. Many come from robotics, autonomous systems, games, finance risk teams and safety-critical software. Privacy engineers add value where scenarios draw on sensitive data.

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 Simulation Scenario Designer

  1. Describe a scenario library you built. How did you decide which conditions it had to cover?

    A strong answer starts from known failures, user risks and system behaviour, then explains how conditions were prioritised. It names who they consulted. Worry if they describe only how many scenarios they generated, or if choices were arbitrary.

  2. How do you show that a synthetic scenario is realistic enough to trust?

    Good answers mix validation against real observations, expert review, distribution checks and automated validators. They admit limits. Worry if they rely on a model's output looking plausible, or if they have never compared synthetic cases with real ones.

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

Job description you can post

We are hiring a Simulation Scenario Designer to build the test scenarios and edge cases we use to find where our AI systems fail. You will work with engineering, product and safety to decide what we must test, build it, and show clearly what we cover and what we do not.

What you will do

  • Design realistic scenarios and edge cases for the systems we build
  • Generate scenarios with generative models and simulators
  • Validate scenarios for realism, diversity and duplication
  • Maintain a versioned scenario library
  • Keep a coverage map of important conditions and known failure modes
  • Turn incidents and failure reports into new scenarios
  • Work with privacy colleagues so synthetic data does not expose sensitive information

What you will bring

  • Built and maintained a scenario, test or simulation suite that others used
  • Experience in experimental design or statistics applied to testing
  • Hands-on work with generative models or simulators
  • Able to explain how you judged coverage and realism
  • Comfortable using dataset validators and writing your own checks
  • Clear communicator with engineering and non-technical colleagues

Nice to have

  • Experience with digital twins
  • Privacy engineering experience
  • Background in safety-critical or autonomous systems testing

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

Skills that matter

  • Synthetic dataAdvancedGenerate test or training examples with validity controls
  • Experimental designAdvancedChoose comparisons that identify credible effects
  • Privacy engineeringWorkingLimit disclosure and unauthorised personal-data use
  • Simulation and digital twinsWorkingBuild useful virtual representations of environments

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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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