Senior Backend Engineer, ML Platform, Tokyo

【Only applicants residing in Japan are eligible to apply.】

About Us

At Money Forward, we are dedicated to transforming financial services using advanced technology. With over 50 services for individuals and businesses, including popular products like Money Forward ME and Money Forward Cloud, we help make managing money easier. We use “account aggregation” technology to gather user data, turning it into useful insights for our customers.

As announced in "Money Forward AI Vision 2026," we view AI utilization not as an option, but as a prerequisite for sustainable enterprise growth. Guided by executive leadership, we are accelerating an all-in AI shift across the entire company.

Rather than treating AI merely as an efficiency tool for existing tasks, we fundamentally ask, "How should this process exist in the first place?" to reconstruct products and workflows optimized for the AI era. Powered by a rich, active user base and vast datasets, we strictly practice AI-driven development engineered backward from maximum user value.

Internally, we actively integrate generative AI tools into our development environments, driving radical productivity gains and rapid product iterations.

We are looking for motivated engineers who want to embrace new technologies without fear of failure in this period of global trial and error—and who are truly passionate about building high-impact AI services grounded in massive real-world data.

Overview

Money Forward is driving company-wide AX (AI Transformation) to deliver "digital workers" — AI agents that carry out business operations autonomously. The CDAO Office leads the AI and data strategy that makes this possible across the entire group.

This is a dedicated backend engineering role owning the application layer of a credit microservice (a private REST API) used across our Digital Bank and group-company fintech products. The microservice combines aggregated data produced by Databricks, machine learning model endpoints on SageMaker, and credit calculation logic inside the service itself to deliver credit information to the product side.

In short, you will turn probabilistic, uncertain model output into deterministic API behavior a financial product can safely depend on.

Our small scrum team is currently focused on developing the credit evaluation model itself. For the FY2027 Digital Bank launch, however, we now need an API designed and built to serve that model's inference results with the traffic capacity and availability the product demands.

Infrastructure, security, observability, and CI/CD are owned by our site reliability / infrastructure engineer, and model development by our machine learning engineers, so you can concentrate on the application itself - but because all three roles collaborate closely, we place real weight on understanding and being able to discuss areas outside your own remit.

Mission Priorities

• Design, build, and assure the quality of a credit microservice (private REST API) capable of supporting the FY2027 Digital Bank launch
• Stabilize machine learning model integration, and secure resilience through latency budgeting and fallback design
• Establish development standards, architecture, and test strategy, and drive the team's technical decision-making

Responsibilities and Duties

As the primary application owner for the microservice, you will take the initiative within our scrum team and:

• Design and implement the microservice architecture: a high-performance, low-latency service in Python and FastAPI, built for transaction volumes at the scale of tens of millions of users, including service boundaries and data ownership.
• Design API contracts and reach agreement with stakeholders: OpenAPI schemas and error taxonomies, versioning and backward compatibility, and the process for changing contracts with Digital Bank and group-company stakeholders.
• Bring models and credit logic into production, with resilience by design: the client-side interface for SageMaker endpoints, latency budget allocation, and timeout, retry, circuit breaker, and fallback behavior.
• Implement credit domain logic with correctness and explainability: credit limit calculation with exhaustive boundary and failure cases, idempotency, reproducibility (linking input data, model version, and logic), and audit trail design.
• Design for performance around data supply: how aggregated data in object storage is loaded, freshness management and consistent cutover, caching strategy, and asynchronous/parallel model calls.
• Own quality, test strategy, and instrumentation: unit, contract, and load testing, regression processes for model swaps, structured logging and traceability, and SLI-driven instrumentation.
• Lead technically and set standards: architecture selection, code review, and improvement and standardization of our development process.

Required Skills and Experience

• 5+ years of professional software engineering experience designing, building, and operating web APIs and microservices in Python or comparable languages
• Track record with high-traffic, low-latency applications through efficient API design and application-level performance tuning
• Contract and failure design experience for external system integrations including API schema, error taxonomy, timeouts, retries, and fallbacks
• Strong test design and quality assurance background with experience embedding automated testing into the development process
• Cloud application development experience on AWS using containerized environments and CI/CD pipelines
• Ability to collaborate and build agreement across roles to drive technical specifications with SRE, machine learning engineers, and external stakeholders

Preferred Skills and Experience

• Knowledge of machine learning integration and MLOps, including calling models on platforms like Amazon SageMaker and designing for inference latency
• Understanding of data platforms and pipelines like S3, Glue, and Databricks to inform technical specs and incident analysis
• Fluency reading and writing IaC with Terraform to propose infrastructure changes via pull requests
• Experience in financial services, credit, or payments domains with exposure to auditability, traceability, and advanced security like mTLS, OAuth, or JWT
• Leadership experience as a tech lead or scrum master with authority over architecture, code quality, and process standardization

Language Requirements

• Business level Japanese (equivalent to JLPT N2 or above)
• Basic business level English (equivalent to TOEIC 700 or above)
• If you do not have a qualification equivalent to TOEIC 700 or above, you will be required to take a company-designated test during the selection process.

Who We’re Looking For

• Wants final accountability for product behavior with first-line responsibility for the correctness, speed, and availability of a credit API designed through to the last failure case
• Drawn to converting the uncertainty of machine learning into the certainty of an API by designing an interface that behaves deterministically despite inference variance, latency, and model updates
• Capable of standing at the boundary between roles to design the collaboration itself through clear ownership while picking up problems that fall between roles
• Thrives on shaping systems during phases of genuine uncertainty and enjoys making the decisions that move projects forward when specifications and architecture are undecided
• Eager to build infrastructure-scale products for the AI era by leading the launch phase of Digital Bank combined with shared credit evaluation using AI development tools such as Claude Code

Technology Stack

• Backend / API: Python (FastAPI), Amazon API Gateway
• Infrastructure / Cloud: AWS (ECS Fargate, S3, CloudWatch)
• ML Serving: Amazon SageMaker (Model Endpoint)
• DevOps / CI/CD: GitHub Actions, Docker, Terraform
• Data Platform (integration target): Databricks, AWS Glue, S3
• AI Development Tools: Claude Code and similar
• Communication / Project: Slack, Notion

Work Environment

At Money Forward, we provide an environment where we can create world-class services together, and we are looking forward to welcoming you.

• Provided PC Specs: We provide PCs equipped with the latest CPUs (MacOS or Windows). Custom-made PCs tailored to business requirements and replacements with the latest OS are also possible.
• Systems to Enhance the Development Environment: Peripheral devices necessary for work (such as displays, mice, keyboards) can be purchased as office supplies. Generally, you can choose from standard products (catalog), and if conditions are met, you can apply for non-standard products as well.
• Money Forward Library: We have a library system where you can freely borrow books, ranging from technical books to management books. Desired books can be purchased at the company's expense.
• Referral Driven: We cover the cost of recruitment meals. There is a referral reward system.
• Conference Participation Support: The company partially covers participation in domestic and international conferences, such as RubyKaigi and Google I/O.

職種 / 募集ポジション

Senior Backend Engineer, ML Platform, Tokyo

雇用形態

正社員

給与

年収 7,008,000円 〜 11,004,000円

Monthly salary system

勤務地

108-0023 21F Tamachi Station Tower S, msb Tamachi, 3-1-21 Shibaura, Minato-ku, Tokyo

Salary System

Salary Range

Min 584,000 JPY / month（7,008,000 JPY / year）- 917,000 JPY / month（11,004,000 JPY / year）

Each including fixed allowances of 170,064 JPY - 266,988 JPY / month.

Bonus

A「High Performance Bonus」may be paid to employees who receive high evaluations based on semi-annual evaluations in addition to their salary.

Probation Period

3 months from join date

Working Hour System

Discretionary Labor System for Professional Work

Working Hours

9:30 - 18:30 (60 min break) are the basic working hours. However, employees are able to choose their working hours at their own discretion.

Work Style Policy

Hybrid work style

• As a standard practice, employees are required to work at the office a minimum of 2 days per week. Employees are encouraged to spend 3 or more days in the office. (This policy may be subject to change based on the company and job circumstances)
• The specific "team office days" may vary depending on the assigned team.

Holidays/Vacations

• Saturdays / Sundays / Japanese national holidays
• Paid holidays
• Summer holidays (3 days)
• Winter holidays (2 days)
• Year-end and New Year’s holidays (Dec 31st～Jan 3rd)

Benefits

• Various social insurances (employee pension, health insurance, employment insurance, industrial accident compensation insurance)
• Neighborhood housing allowance and neighborhood moving allowance
• Health check and gynecological checkup
• Influenza vaccine
• Book purchases support
• Defined-contribution corporate pension
• Employee stock ownership plan

Preferential treatment when using the following services（limited to businesses under contract with Money Forward）

• Rental agency
• Housekeeping services
• Babysitting
• Online English conversation school

Selection Process１

Casual interview/Document Screening

First interview (Depending on the position, there may be a technical assignment before the interview.)

Several interviews (The number of interviews depends on the position. We will request you to take an aptitude assessment.)

Final interview (We may ask for a reference check before or after the interview.)

Job offer/Offer meeting

Selection Process２

About the Aptitude Test

It is a simple web-based survey taking around 20 minutes to complete.

What are reference checks?

Money Forward may ask for your cooperation with reference checks using a reference check service tool. We believe that mutual understanding is limited to the selection process alone. Therefore, we would like to gather information about you from your supervisor and colleagues at your current or former company to ensure a more reliable match and facilitate your early success after joining our company.

Notes

• Range of change in job description: Work as determined by the company
• Range of change in work location: Work location as determined by the company

Reference Information

recruit.moneyforward.com/#introduction

会社情報

会社名

株式会社マネーフォワード

代表者

代表取締役社長グループCEO 辻 庸介

創業

2012年5月

取締役

金坂 直哉

中出 匠哉

竹田 正信

石原 千亜希

社外取締役

安武 弘晃

宮澤 弦

Ryu Kawano Suliawan

菊間 千乃

芦田 健

上田 梨々子

監査役

畠山 優実

田中 克幸

西山 茂

グループCxO・VPox

上利 陽太郎

瀧 俊雄

山田 一也

坂 裕和

松岡 俊

伊藤 セルジオ 大輔

関田 雅和

松久 正幸

野村 一仁

長尾 祐美子

金井 恵子

梅田 康吉

丸山 嘉伸

執行役員

田平 公伸

本川 大輔

冨山 直道

永井 博

駒口 哲也

廣原 亜樹

島村 誠一郎

永井 七奈

木村 慎治

吉本 憲文

工藤 裕之

島内 広史

小山 幸宏

渡辺 恵伍

松村 道夫

岩崎 大

渋谷 亮

オフィス

本社オフィス

〒108-0023 東京都港区芝浦3-1-21 msb Tamachi 田町ステーションタワーS 21F

北海道支社

〒[phone removed] 北海道札幌市中央区南一条西4-5-1 札幌大手町ビル3階

東北支社

〒980-0021 宮城県仙台市青葉区中央2-2-10 仙都会館 5F

東海支社、名古屋開発拠点

〒450-6213 愛知県名古屋市中村区名駅4-7-1 ミッドランドスクエア 13F

京都支社、京都開発拠点

〒604-8004 京都府京都市中京区三条通河原町東入中島町78番地 明治屋京都ビル 4階

関西支社、大阪開発拠点

〒541-0042 大阪府大阪市中央区今橋 2-5-8 トレードピア淀屋橋 9階

広島支社

〒730-0015 広島市中区橋本町9-7 ビル博丈5F

九州・沖縄支社、福岡開発拠点

〒810-0041 福岡県福岡市中央区大名2丁目6-50 福岡大名ガーデンシティ 16F

社内コミュニケーション活性化の取り組み

• 全社週次/月次朝会/半期総会
• 代表との意見交換会（CEOセッション）
• 全社懇親会（MF Happy Hour）
• 他部門社員との交流会（シャッフルランチ・ディナー）
• 上長との定期1on1（ツキイチ面談）
• 社内公募制度（MFチャレンジシステム）
• 社員満足度調査（MFグループサーベイ）

労働条件

屋内原則禁煙（喫煙室あり）等

中途採用比率

2021年11月末 93.8％

2022年11月末 90.0%

2023年11月末 76.6％

2024年11月末 88.7%