Jalasoft
Jalasoft
Jalasoft एक नियरशोर सॉफ्टवेयर डेवलपमेंट कंपनी है, जो दक्षिण अमेरिका में स्थित टीमों और 13 देशों के 70 शहरों में अपनी व्यापक उपस्थिति के माध्यम से ग्राहकों को सेवाएँ प्रदान करती है। इसके 1,000 से अधिक इंजीनियर सॉफ्टवेयर डेवलपमेंट, क्वालिटी एश्योरेंस और DevOps के क्षेत्रों में काम करते हैं तथा स्टाफ ऑगमेंटेशन और समर्पित टीमों, दोनों तरह की सेवाओं का समर्थन करते हैं। Jalasoft सुरक्षित प्रौद्योगिकी डिलीवरी पर भी ध्यान केंद्रित करती है और नेटवर्क व डेटा सेंटर प्रबंधन के लिए ISO 27001 प्रमाणन तथा Palo Alto, NVIDIA और Cisco से जुड़ी साझेदारियों का लाभ उठाती है। Jala University के माध्यम से कंपनी ऐसे प्रौद्योगिकी शिक्षा कार्यक्रम विकसित करती है, जो नई तकनीकी प्रतिभाओं को तैयार करने और आकर्षित करने में मदद करते हैं। सॉफ्टवेयर, QA, DevOps, SaaS या प्रौद्योगिकी शिक्षा के अवसर तलाशने वाले पेशेवरों के लिए Jalasoft इंजीनियरिंग सेवाओं, प्रतिभा विकास और डिजिटल परिवर्तन कार्यों से जुड़ी एक व्यापक कंपनी प्रोफ़ाइल प्रस्तुत करती है।

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.

विवरण

  • 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

आवश्यकताएँ

  • 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

लाभ

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

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