Applied AI Engineer at BJAK

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Build production AI agents and financial workflow automations using LLMs, retrieval and evaluations. Requires practical engineering experience with AI systems, strong coding skills and strong English communication. This is a production-building role, not research only.

BJAK

Search jobs by company: BJAK

Location: Remote
Advertised region: Vietnam · Remote · Must already be based in Vietnam
Work arrangement: remote
Technologies: AI, Python, TypeScript, JavaScript

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Role overview

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.

People who only want research projects with no production ownership.

Candidates who treat AI as demos instead of working systems.

Responsibilities

Build AI agents, workflows, tools and automations that solve real customer, product and operations problems.
Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows.
Create AI-assisted experiences for onboarding, Help with, KYC, risk review, CRM, operations, document handling and product intelligence.
Work with product and engineering teams to identify what is worth building, then build it quickly and improve it in production.
Design around real constraints: accuracy, hallucination risk, latency, cost, security, compliance and user trust.
Turn manual processes into reliable AI-enabled systems that can scale.

Qualifications

Hands-on engineering ability, not just AI strategy or management experience.
Experience building AI agents, LLM apps, RAG systems, automation workflows, copilots or AI-enabled tools.
Strong coding ability in Python, TypeScript, JavaScript or similar practical stack.
Good judgement on what should be automated and what should not.
Able to ship working systems, test quality and improve reliability over time.
Fintech, banking, Help with automation, risk, KYC, fraud, CRM or operations automation experience is a strong plus.

Technology in this role

AI: AI Python TypeScript .
Python: AI Python TypeScript .
TypeScript: AI Python TypeScript .
JavaScript: AI Python TypeScript .
LLM: Experience building AI agents, LLM apps, RAG systems, automation workflows, copilots or AI-enabled .
RAG: Experience building AI agents, LLM apps, RAG systems, automation workflows, copilots or AI-enabled .
CAN: We need builders who can use AI to automate real workflows, improve products, reduce manual work and make financial services easier for users and .

Role-specific candidate guide

Preparation notes based on the employer’s stated responsibilities and qualifications.

Understanding the scope. This Applied AI Engineer position at BJAK is best assessed through the work described in the employer’s posting, rather than the title alone. The available role overview says: “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…” Read that statement together with the responsibilities below to understand the likely balance between delivery, coordination and technical decision-making. The role belongs to the AI and data area, but that label is only a guide to the work; the employer’s own requirements remain decisive. Before applying, check the original listing for reporting lines, product or team assignment, employment terms and any details that may have changed since this copy was checked. Where this page says a fact is not specified, treat it as an open question rather than an implied promise.

What the responsibilities signal. The posting specifically names “Build AI agents, workflows, tools and automations that solve real customer, product and operations problems.”; “Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows.”; “Create AI-assisted experiences for onboarding, Help with, KYC, risk review, CRM, operations, document handling and product intelligence.”. For each duty, identify a project where you performed comparable work and be ready to describe the context, your own contribution, constraints, decisions, and measurable result. Explain how you moved from the initial need to implementation, review, release or operational follow-through, where those stages apply. If the work involved other teams or users, distinguish your decisions from the group’s contribution. Avoid presenting a technology keyword as proof by itself: connect it to the problem you solved, the scale or complexity involved, and what changed after your work. The source may contain additional duties; review it directly before preparing your application.

How to read the requirements. The listed qualifications include “Hands-on engineering ability, not just AI strategy or management experience.”; “Experience building AI agents, LLM apps, RAG systems, automation workflows, copilots or AI-enabled tools.”; “Strong coding ability in Python, TypeScript, JavaScript or similar practical stack.”. Mark each requirement as demonstrated, adjacent experience or a genuine gap, then use a concise example for the first two categories. A strong example explains what you personally owned, how you made trade-offs, how you validated the result and what you learned. If the posting specifies years of experience, language ability, certifications, location or eligibility, address those facts plainly in your CV or application rather than relying on the employer to infer them. Do not claim a qualification from exposure alone. For a requirement you do not meet, describe relevant transferable experience accurately and ask the recruiter whether it is mandatory.

Technology and working evidence. The technology terms associated with this listing are AI, Python, TypeScript, JavaScript. Treat this as a set of posting-derived signals, not a guarantee that every tool is used daily or that.