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Open nowPosted 3 days ago

Academic Content Developer - AI & Fraud Detection in Financial Systems (FinTech)

Workable (global search)108,016 open roles

Where
Argentina
Work mode
Remote
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Your applicationOpen nowAcademic Content Developer - AI & Fraud Detection in Financial Systems (FinTech)Workable (global search) · Argentina

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Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 3 days ago

Workable (global search) median: 7 days open

The posting

Jala University is an innovative initiative designed to bridge the gap between academia and industry by delivering practical education tailored to industry needs, with a unique educational model integrating experts from both academia and industry.

Our goal is to transform the economies of underserved regions through the software industry, creating professional opportunities that impact individuals, communities, and regions, while leaving a lasting legacy for future generations

We're looking for a content developers for Fintech Engineering Specialization at Jala University. You'll design module content, labs, a reference implementation, an evaluation harness, and an instructor guide.

Requirements

Mandatory

  • Has worked on a fraud/risk team at a fintech operating at scale (Nubank, Mercado Pago, Rappi, or similar)
  • Public writing samples showing technical explanation (docs, workshop material, book chapter, or open-source project known for its docs), including ability to write to publication standard
  • Reproducibility discipline (pinned dependencies, containers, seeded runs, documented decoding parameters)
  • Professional written English

Experience

  • 5+ years as a software engineer
  • 3+ years in FinTech, payments, or financial services

Tech stack

  • Go
  • TypeScript / Node.js

Key technical requirements

  • Real-time fraud pipelines: streaming, rules + ML with latency SLAs
  • Integration with fraud providers (Cybersource, ClearSale, Fingerprint, Seon)
  • ML from the perspective of the engineer integrating models, including feature engineering
  • Feature Stores
  • KYC/AML, sanctions and PEP lists, COAF or UIF reporting
  • Treasury reconciliation (proof of reserves)

Nice to have

  • Master's Degree in Computer Science or related.
  • Production experience with blockchain transaction monitoring / crypto AML
  • Model explainability in regulated LatAm markets

Benefits

  • Remote work modality (home office).
  • Joining a dynamic and growing organization with international reach.
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