Jalasoft
Jalasoft
Jalasoft ir nearshore programmatūras izstrādes uzņēmums, kas apkalpo klientus, izmantojot Dienvidamerikā bāzētas komandas un plašāku klātbūtni 70 pilsētās 13 valstīs. Vairāk nekā 1 000 uzņēmuma inženieru strādā programmatūras izstrādes, kvalitātes nodrošināšanas un DevOps jomā, nodrošinot gan personāla papildināšanas, gan specializētu komandu pakalpojumus. Jalasoft pievēršas arī drošai tehnoloģiju ieviešanai — uzņēmumam ir ISO 27001 sertifikāts, kā arī partnerības ar Palo Alto, NVIDIA un Cisco tīklu un datu centru pārvaldības jomā. Ar Jala University starpniecību uzņēmums izstrādā tehnoloģiju izglītības programmas, kas palīdz attīstīt un piesaistīt jaunus tehniskos talantus. Profesionāļiem, kurus interesē programmatūra, kvalitātes nodrošināšana, DevOps, SaaS vai tehnoloģiju izglītība, Jalasoft piedāvā uzņēmuma profilu, kas aptver inženiertehniskos pakalpojumus, talantu attīstību un digitālo transformāciju.

Academic Content Developer, AI Fraud Detection and Financial Systems

Develop FinTech fraud-detection curriculum for Jala University, covering instructional modules, practical labs, reference implementations, evaluation tooling, and instructor documentation.

Apraksts

  • Create module content for Jala University's FinTech Engineering Specialization
  • Develop practical laboratory exercises
  • Produce a reference implementation
  • Build an evaluation harness
  • Write an instructor guide

Prasības

  • Experience on a fraud or risk team at a large-scale fintech such as Nubank, Mercado Pago, Rappi, or a comparable company
  • Public technical writing samples—such as documentation, workshop materials, a book chapter, or a documentation-focused open-source project—written to publication standard
  • Strong reproducibility practices, including pinned dependencies, containerization, seeded runs, and documented decoding parameters
  • Professional written English proficiency
  • At least 5 years of software engineering experience
  • At least 3 years of experience in FinTech, payments, or financial services
  • Go programming experience
  • TypeScript and Node.js experience
  • Experience with real-time fraud pipelines, including streaming, rules-based systems, machine learning, and latency SLAs
  • Experience integrating fraud providers such as Cybersource, ClearSale, Fingerprint, or Seon
  • Understanding of machine learning from the perspective of an engineer integrating models, including feature engineering
  • Experience with feature stores
  • Knowledge of KYC/AML processes, sanctions and PEP lists, and COAF or UIF reporting
  • Experience with treasury reconciliation and proof-of-reserves processes

Priekšrocības

  • Remote work from a home office
  • Opportunity to join a dynamic, growing organization with international reach

Saistītās vakances