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BJAK

Applied AI Engineer - AI Neobank App (India)

Posted 7 Days Ago
Remote
Hiring Remotely in India
Mid level
Remote
Hiring Remotely in India
Mid level
Build and productionize AI-native systems (workflows, assistants, agents) across fintech/insurance product areas. Integrate LLMs with data, APIs and business systems, design monitoring and fallback flows, prototype quickly, and improve operational quality and automation.
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About BJAK

The original mission of BJAK is we believe people deserve smarter ways to plan, save and grow their money. This is the origin of our name.
Started in 2019, we built the first mobile-first, insurance platform, enabling insurance to be accessible online by millions in the region. Today, its the leading insurance platform in Southeast Asia.
Today, we are expanding ways to help people in the region — this includes spending, saving, investing, exchanging, travelling, and more. Our mission is help people get more from their money every day.
We have teams working around the world, with over 20 nationalities from our offices and remotely, who truly enjoys their work. We are looking for the most talented and driven people we can find. We are looking for people who work for their passion, not counting hours. Who loves building great next-generation products, not status quo. Who cares about redefining how everyone around us can get the best financial applications, not for an exclusive few.
If you're this person, we'd love to talk to you.

 
The Role

We are looking for applied AI engineers to build AI-native systems for BJAK's AI Neobank app.
This is not a research-only role. We need builders who can use AI to automate real workflows, improve products, reduce manual work and make financial services easier for users and teams.

 
What You'll Own
  • Build AI-powered workflows, assistants, agents and automation systems.

  • Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools.

  • Work with product and engineering teams to turn manual processes into scalable AI-native systems.

  • Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems.

  • Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable.

  • Prototype quickly, test with users or operators, then productionize what works.

  • Improve speed, quality and consistency across workflows using AI where it creates real business value.

 
What We're Looking For
  • Strong software engineering foundation, preferably with Python and backend systems.

  • Hands-on experience building with LLM APIs, agents, RAG, workflow automation or AI tools.

  • Able to connect AI systems with real product, data and operational workflows.

  • Good judgement on where AI helps and where rule-based systems or human review are better.

  • Understands evaluation, accuracy, latency, cost, privacy and failure modes.

  • Fast builder who can prototype, test and ship practical systems.

  • Experience in fintech, insurance, support automation, CRM or operations automation is a strong advantage.

 
The Kind of Builder We Want
  • Practical AI builder, not just a prompt experimenter.

  • Thinks in workflows, systems and measurable quality.

  • Can build quickly but still cares about guardrails and reliability.

  • Comfortable working with messy real-world data and processes.

  • Honest about what AI can and cannot do.

 
This Role Is Not For
  • People who only want research projects with no production ownership.

  • Candidates who treat AI as demos instead of working systems.

  • Engineers who do not care about evaluation, reliability or user impact.

  • People who overclaim AI impact without evidence.

  • Builders who cannot work with product, ops and business teams.

 
Location

This role is remote, but candidates must be based in India. We are hiring specifically for this market, so applicants should already be based in India.

 
Language

English is our main working language across global teams. Strong English communication is required.

 
Interview Process

Our process is designed to move fast:

1. Online assessment or practical task

2. Technical interview

3. CEO / final round

For strong candidates, we aim to complete the process and make an offer within 1 week from the start of the interview process. Candidates who complete assessments quickly will be prioritized.

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