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 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.
Responsibilities
- 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.
Requirements
- 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
Nice to haves
While not specifically required, tell us if you have any of the following.
- 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
Compensation
¥7,008,000 ~ ¥11,004,000 annually.
