Senior Backend Engineer, ML Platform, Tokyo

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

Overview

Guided by Money Forward AI Vision 2026, 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.

Success is clearly defined: ensuring the FY2027 Digital Bank launch succeeds, from the standpoint of the credit microservice. Your mission is the architecture, implementation, and quality assurance that work backward from it.

Mission Priorities

1. Design, build, and assure the quality of a credit microservice (private REST API) capable of supporting the FY2027 Digital Bank launch
2. Stabilize machine learning model integration, and secure resilience through latency budgeting and fallback design
3. 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.

※Please note that the interviews in the selection process will be conducted in Japanese.

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.