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BRG

Global consulting transforming data into insights

Associate Director AI Product Engineer - Financial Institution Operations & Technology

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA$180k - $250k

About the Job

Requirements

  • Minimum 5 years of working experience, including a minimum of 1 year of experience in AI evaluation.
  • Demonstrated ownership of AI evaluations that informed real release decisions, including test design, expert-reviewed answers, scoring, and failure investigation.
  • Strong Python skills and experience building automated test software, connecting data sources, and recording repeatable results across product versions.
  • Ability to select representative samples, interpret error rates and uncertainty, and distinguish genuine improvement from weak tests or inconsistent scoring.
  • Experience building or improving AI products used in operations, with practical controls for sensitive data, output accuracy, and human review.
  • Experience in financial services or another regulated environment, with the ability to translate business requirements into practical tests and controls.
  • Ability to mentor colleagues and willingness to travel to client sites as needed.

Responsibilities

  • Define what each product must get right, how errors could affect customers or operations, and what evidence is needed before use.
  • Build reusable software that runs tests, scores results, and compares versions, making testing part of everyday development rather than a final checkpoint.
  • Work with engineers to reproduce failures, identify causes, and verify fixes; contribute product code where needed to improve accuracy and control.
  • Set pass criteria and scoring rules with business and risk teams, distinguishing minor defects from errors that must block release.
  • Maintain representative test cases, including incomplete records and rare, high-impact errors, and reserve unseen examples for final testing to avoid overstating performance.
  • Have banking experts establish expected answers and resolve scoring disagreements; measure factual accuracy, missing information, incorrect additions, and support from cited sources.
  • Check automated scoring against expert review, test whether reviewers agree, and assess whether AI-based scoring misses important errors.
  • Compare versions on the same tests and report results by task and error severity, with sample sizes and uncertainty rather than averages alone.
  • Test whether the system finds the right information and whether its answer reflects that information, separating source problems from answer errors.
  • Check extracted facts against original records; independently verify amounts, dates, and totals; and test whether citations support each important claim.
  • Test when the product should answer, request clarification, or refer work to a person, and verify that reviewers can detect and correct material errors.
  • Test for invented facts, unsupported recommendations, unfair outcomes, disclosure of sensitive information, and attempts to make the system ignore its safeguards.
  • Protect client data, restrict access and permitted actions, use only approved services, and verify that safeguards work in practice.
  • Document repeatable test results, unresolved failures, and limitations; recommend release, restricted use, or further development; and support independent review and required client approvals.
  • Sample live outputs and track error rates and user corrections; add confirmed failures to repeatable tests; and trigger investigation or suspension when quality falls below agreed standards.
  • Explain findings clearly, coach colleagues, develop reusable tests and controls, and support proposals, technical estimates, and recruiting.

Desired Qualifications

  • Banking experience in lending, payments, servicing, collections, or default operations.
  • Experience independently evaluating AI products, checking automated scoring against expert judgment, or testing security and fairness in financial institutions.
  • Experience evaluating document review, summaries, information search, or automated workflows, including comparisons across AI services and conventional software.
  • Consulting or product delivery experience, including client discovery, implementation planning, and user adoption.

About the Company

BRG

Global consulting transforming data into insights

ThinkBRG provides professional advisory and consulting services worldwide, focusing on turning raw data into actionable insights for clients across many industries. Its approach combines data analysis with expert consulting to help organizations make better decisions. The process relies on a collaborative, globally distributed team that shares knowledge daily to produce high-quality insights tailored to each project’s complexity, expertise needs, and duration. ThinkBRG differentiates itself through deep industry understanding, a proven track record, and a global footprint that enables serving a diverse client base from small businesses to large corporations. The company’s goal is to help clients transform information into practical recommendations and actions that drive decision-making and measurable outcomes, generating revenue through consulting engagements aligned with project scope and duration.

Company size
1,001-5,000
Company stage
Late Stage VC
Total funding
$84.5M
Headquarters
Emeryville, CA
Founded
2010

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