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Bjak

Applied AI Engineer - AI Neobank App (US)

United States (Remote)fulltimemidAdded today

About this role

BJAK is hiring an Applied AI Engineer to build AI-native systems for their neobank app, automating workflows across customer support, onboarding, claims, and operations. You'll integrate LLMs and AI agents into real financial products, balancing speed with reliability and measurable business impact.

What you'll do

  • Build AI-powered workflows, agents and automation systems for customer support, CRM, onboarding, claims, renewals and payments
  • Integrate LLM APIs, RAG systems and internal data sources with business workflows and APIs
  • Design evaluation metrics, monitoring and fallback flows to ensure AI outputs are safe, reliable and useful
  • Prototype quickly, test with users or operators, then productionize working solutions
  • Partner with product and engineering teams to transform manual processes into scalable AI-native systems
  • Optimize for speed, quality and cost across workflows using AI where it creates real business value

What they're looking for

  • Python and backend systems development
  • LLM APIs, agents, RAG and workflow automation
  • AI evaluation, accuracy metrics and failure mode analysis
  • System design and integration with data, APIs and business systems
  • Prototyping and rapid iteration
  • Fintech, insurance or operations automation experience
  • SQL and data work
  • Cross-functional collaboration with product and ops teams
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Bjak

Bjak is a Southeast Asian fintech super app offering insurance, payments, savings, wallets, and investment products through a unified platform. The company is hiring full stack engineers, backend engineers, iOS developers, and Android engineers to build scalable features and reliable systems across mobile and web products.

Website
bjak.com
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Likely interview questions

  • Walk us through a specific AI system you built end-to-end—from prototype to production—and how you measured its business impact.
  • Describe a time you had to decide whether to use AI or a rule-based system for a workflow. What factors influenced your decision?
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