[HCM] AI Product Builder (Java, AI)

Money Forward Vietnam Co., Ltd; Maiori; On-site; EUR 90,000 - 140,000; Full time

Job summary

Money Forward Vietnam Co., Ltd is scaling product development with generative AI. In this role you turn ambiguous intent into working prototypes and handoffs to engineering, bridging product, UX and engineering.

You will design AI agents, workflows, and multi-step processes, using LangChain, LlamaIndex, and no-code/low-code tools to ship production-grade prototypes quickly, with security and data privacy at the forefront.

Qualifications

• 8+ years in software development across backend and frontend.
• Proven ability to translate high-level requirements into detailed technical specs.
• Strong verbal and written English for distributed teams.
• Prototyping and product iteration using AI tools and no-code/low-code.

Responsibilities

• Design and orchestrate AI agents, skills, and multi-step workflows.
• Translate business requirements into explicit UX flows, data contracts, and specs.
• Develop end-to-end apps using AI-enabled tech and hybrid coding.
• Ship production-ready code and documentation for handover to engineering.
• Drive CI/CD, monitoring, and security within prototypes.

Skills

Generative AI

AI Agents & Workflows

AI-assisted development

Software engineering

Frontend & Backend

English communication

Agile (Scrum/Kanban)

Tools

LangChain

LlamaIndex

Semantic Kernel

GitHub Copilot

Cursor

Claude

ChatGPT

Job description

We are scaling product development alongside the evolution of generative AI. In this role you turn ambiguous intent into working prototypes and high-fidelity handovers to engineering. You operate in a paradigm shift toward meta-engineering: orchestrating generative AI, prompts, and tools—not only hand-coding from static specs—while our products address B2B back-office domains (e.g., accounting, HR) and rising expectations for clarity, speed, and a credible path to scale.

About the role

An implementer who takes direction from product and domain experts, uses generative AI (LLMs), no-code/low-code, and hands-on engineering to move from “what to build” to working prototypes and initial implementations in days—not weeks. This role bridges product, UX, and engineering: you shape the “how” at maximum speed, then hand off testable, specified work to the broader engineering organization.

This role expects a strong security mindset, with a clear understanding of data privacy, credential protection, device security, and the responsible use of corporate systems, tools, and accounts.

Responsibilities

1. AI & System Design

• Design and orchestrate AI agents, skills, and multi-step workflows integrated into micro-services and frontend architectures.
• Translate business requirements and domain constraints into explicit UX flows, data contracts, and technical specifications.
• Develop end-to-end applications and features using Java/Kotlin, Spring Boot, and React JS.
• Build rapid, functional prototypes and vertical slices using a hybrid of custom code, AI-assisted tools, and low-code solutions to validate concepts quickly.
• Package and deliver production-ready, testable code and documentation for seamless integration into the broader engineering ecosystem.
• Analyze, refactor, and extend legacy codebases using AI-driven diagnostic and coding tools.
• Drive continuous improvement across the engineering stack by pioneering new AI development methodologies, templates, and platforms.

4. Key Enhancements Made

• Technical Integration: Linked standard engineering tools (Spring Boot, React) directly to AI workflows so candidates know they will write real code, not just build prompt chains.

You are not only a prompt author: you ship full-stack software and can own thin slices end-to-end when the prototype must be real.

• End-to-end feature development: backend services and SPAs; comfort moving across the stack for prototypes and v1 implementations.
• Backend: strong hands-on skills in Java or Kotlin; RESTful APIs; sound approach to micro-services and backward compatibility where relevant; performance, concurrency, and clean structure in code.
• Data: strong SQL skills and query tuning; ACIDaware design for transactional behaviour in prototypes.
• Delivery: CI/CD (e.g. GitHub Actions, CircleCI, or similar), Git workflows, code review habits; AWS and Docker for deployable prototypes; Kubernetes exposure is a plus.
• Reliability and security in scope of the prototype: authentication/authorization patterns, JWT/OAuth2 at a level appropriate to demos and handover notes; SLO/SLI thinking and observability hooks where the prototype will graduate.
• Leadership of craft: contribute to architecture for your domain verticals; mentor others; incident mindset (when things break, fix and document).

Required experience and skills (must have)

• Generative AI:

+ Agentic Frameworks & Workflows: Hands-on experience designing and orchestrating AI agents, custom skills, and multi-step workflows (e.g., via LangChain, LlamaIndex, Semantic Kernel, or similar frameworks/tools).

+ AI-Assisted Development: Advanced proficiency with AI-driven coding tools (e.g., GitHub Copilot, Cursor, Claude, ChatGPT) to accelerate system design, debugging, and code generation.

• Substantial software engineering and/or product-minded UI/UX delivery—you build things yourself, not only describe them. 8+ years in software development including both backend and frontend experience is the target bar for this principal-level scope.
• Product mindset: Proven track record translating high-level product requirements into detailed requirements and comprehensive technical requirements through close partnership with Product Managers and domain stakeholders.
• Communication: Strong verbal and written English for clarity and alignment in distributed, multinational product engineering teams.
• Prototyping and product iteration using AI tools and no-code/low-code, grounded in user and operational workflow understanding.
• Comfort with ambiguity: ship “something that works first,” then refine in tight loops (agile execution).
• Track record as a central technical contributor on product initiatives that reached users and business outcomes.
• Agile familiarity (Scrum/Kanban); strong problem-solving across technical and product uncertainty.

Preferred (nice to have)

• Micro-frontends, state machines, advanced Golang or Java concurrency.
• Kubernetes, Kafka/RabbitMQ, Prometheus/Grafana/ELK or similar.
• DDD, Clean/Hexagonal architecture; experience in accounting, finance, or other domain-heavy B2B products.
• Open-source or strong continuous learning profile.
• Japanese language skills (not required) — a strong plus for collaboration with Japan-based teams, product, and stakeholders.