AI Testing Assistant
Mosaic Conseil
Description
About Mosaic Conseil
We are a boutique consultancy that values intellectual honesty and the discipline of a small, focused team. By staying small and fully remote, we remain independent and focused on the evidence at the floor of the business. Our clients come to us when they need a business plan or a financial model rebuilt with extreme precision. We provide a workspace where the primary goal is getting the numbers and the logic right, rather than making things look good in a presentation. Every file that leaves our workshop carries two names on the cover: one person who builds and one who argues against what was built. This ensures that every assumption is tested before a file closes. This environment is built for thinkers who prefer a written argument over a status meeting.
What you would do
As an AI Testing Assistant, your work focuses on the intersection of business logic and automated analysis. You will be responsible for testing the outputs of AI models used to process financial and industrial data. This is an entry level role where you support our consultants by stress testing the artifacts we build. Your day to day work involves:
- Reviewing AI generated summaries and data extractions for accuracy against original source documents like ledgers or contracts.
- Running standardized tests on internal AI tools to identify where they fail to grasp complex financial logic or industrial constraints.
- Building simple test cases to verify that a pricing model or a business plan remains consistent when variables are changed.
- Documenting specific instances of model error or hallucination in a clear, written format.
- Assisting the challenger in our builder and challenger model by providing evidence of where an automated calculation may have deviated from the truth.
- Comparing different AI model outputs to see which one handles specific industry terminology from healthcare or industrial networks more reliably.
- Verifying that the data used for a specific business artifact has been correctly mapped by our automated scripts.
We are looking for individuals who have a natural curiosity about how technology works and, more importantly, how it breaks. This role is accessible to those starting their career or looking for part time work while finishing their studies. Helpful traits and experiences include:
- Basic familiarity with Large Language Models and an understanding of how to prompt them for technical tasks.
- Competence in using spreadsheets like Excel or Google Sheets to verify calculations.
- Strong writing skills and the ability to explain a technical error in plain English.
- A background in business, finance, or computer science is useful but we value the ability to follow a logical argument above a specific degree.
- Technical comfort with remote work tools and a disciplined approach to managing your own schedule.
- Experience with personal projects or academic work that involves data analysis or AI testing.
- An interest in the specific sectors we serve, particularly financial services and industrial networks.
Our workshop is entirely remote, meaning you can work from wherever you are most productive. We do not have an office and we do not hold meetings unless they are strictly necessary for the work. We communicate primarily through written documents and internal notes. Our builder and challenger model means that your work as a tester is central to our reputation. You are not just a support person: you are an essential part of the verification process that allows us to stand behind every artifact we produce. We prioritize deep work and give our team the quiet they need to find the errors that others miss. There is no requirement for residency in a specific city or country, as we operate a global, decentralized bench.
What the role offers
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About Mosaic Conseil
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Interview Prep Guide
Preparation Strategy
To prepare for this role, review your experience with technical testing, AI models, and data analysis. Practice explaining technical concepts in plain English and be prepared to give specific examples of your experience with these topics. Additionally, review your knowledge of business and finance concepts, as well as your ability to work independently in a remote environment. It's also important to demonstrate your curiosity about how technology works and your ability to identify errors and inconsistencies in technical systems.
Likely Interview Rounds
- 1. Screening call~30 min
What to prep: Review your experience with AI models, Large Language Models, and technical testing. Be prepared to give specific examples of times when you identified errors or inconsistencies in technical systems.
- Can you give an example of a time when you identified an error in a technical system?
- How do you approach testing the outputs of AI models?
- What experience do you have with Large Language Models?
- 2. Technical~60 min
What to prep: Review your knowledge of technical testing, AI models, and data analysis. Practice explaining technical concepts in plain English and be prepared to give specific examples of your experience with these topics.
- How would you test the accuracy of an AI-generated summary against an original source document?
- What methods would you use to identify errors in a pricing model or business plan?
- Can you walk me through your process for verifying calculations in a spreadsheet?
- 3. Behavioral~60 min
What to prep: Review your experience working in a remote environment and your ability to communicate technical concepts to non-technical people. Be prepared to give specific examples of times when you demonstrated these skills.
- Can you tell me about a time when you had to explain a technical concept to a non-technical person?
- How do you handle working independently and managing your own schedule in a remote work environment?
- What motivates you to work in a role that involves testing and verifying technical systems?
Most Likely Questions
- What do you know about our company and our approach to business?
- How do you think your skills and experience align with this role?
- Can you give an example of a time when you identified an error or inconsistency in a technical system?
- How do you approach testing and verifying technical systems?
- What experience do you have with Large Language Models and AI models?
Common Pitfalls
- Lack of attention to detail when reviewing technical systems
- Inability to communicate technical concepts in plain English
- Insufficient experience with Large Language Models and AI models
- Difficulty working independently in a remote environment
Free Prep Resources
- • LeetCode
- • Kaggle
- • Coursera - Machine Learning course
- • edX - Data Analysis course