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Bjak

Applied AI Engineer (Austria)

Global (Remote)fulltimemidAdded today

About this role

BJAK seeks an applied AI engineer to build production AI systems for their neobank platform, focusing on practical automation of financial workflows like KYC, support, and operations rather than research-only projects. You'll work with LLMs, agents, and RAG systems to solve real customer and operational problems at scale.

What you'll do

  • Build AI agents and workflows that automate customer onboarding, support, KYC, risk review, and document handling
  • Apply LLMs, retrieval, tool calling, and guardrails to practical financial use cases while managing hallucination and accuracy risks
  • Design AI-assisted experiences balancing reliability, latency, cost, security, and compliance constraints
  • Partner with product and engineering teams to identify high-impact problems and ship solutions quickly
  • Transform manual processes into reliable, scalable AI-enabled systems
  • Evaluate and improve system quality and reliability in production environments

What they're looking for

  • Python, TypeScript, or JavaScript development
  • LLM applications and AI agent architecture
  • RAG (retrieval-augmented generation) systems
  • Prompt engineering and LLM evaluation
  • API integration and tool calling
  • Production system reliability and monitoring
  • Fintech or financial services domain knowledge (preferred)
  • Automation workflow design
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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

  • Can you walk us through a production AI system you built end-to-end, including how you handled accuracy, latency, and cost tradeoffs?
  • How do you approach building guardrails and preventing hallucinations in LLM applications for high-stakes domains?
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