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Commercial Banking — Expert AI Trainer

Job Overview

Location

London

Job Type

Contract

Category

Product Management

Date Posted

April 11, 2026

Full Job Description

📋 Description

  • This role is a Commercial Banking Expert AI Trainer residency at Mentis Technology Solutions Inc., designed for senior banking professionals to shape how AI systems reason and make decisions in high-stakes financial environments by applying deep domain expertise to improve AI relevance and reliability.
  • Day-to-day responsibilities include developing realistic prompts to test AI-generated insights, comparing human versus machine judgment in investment reasoning, designing frameworks that translate commercial banking operations (client access, loan structuring, balance sheet and risk management) into AI challenges, and constructing expert benchmarks using real-world credit cases and portfolio management frameworks to evaluate frontier AI systems.
  • Mentis AI operates at the intersection of institutional investment expertise and frontier AI, combining deep asset management experience from firms like Lazard and Partners Group with machine learning research. The team collaborates with leading AI labs across London and San Francisco to advance AI’s ability to reason in complex financial contexts.
  • In this role, you will gain hands-on experience influencing the direction of AI in banking, develop expertise in AI evaluation methodologies, contribute to cutting-edge AI safety and alignment efforts in finance, and build a bridge between traditional banking expertise and advanced AI systems—positioning you at the forefront of AI adoption in institutional finance.

Skills & Technologies

Remote

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About Mentis Technology Solutions Inc.

Mentis provides enterprise data-centric security solutions focused on dynamic data masking, sensitive data discovery, database activity monitoring, and compliance reporting. Founded in 2004, the company serves Fortune 500 organizations and government agencies worldwide, helping protect structured and unstructured data across relational databases, big data platforms, and mainframe environments through continuous classification, real-time masking, and risk analytics without altering source data or impacting performance.

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