Resume

Basic Information

Field	Details
Name	Yasuo Nonaka
Date of Birth	July 1993
Location	Tokyo, Japan
Education	Ritsumeikan University Graduate School, Business Administration (MA)
Certifications	Ordinary Driver’s License, Securities Analyst (Japan), Level 2 Bookkeeping (Japan)

Professional summary

I am a full-stack engineer with over eight years of experience, centered on Python and TypeScript.

I work across the stack from frontend (Next.js, Vue.js, React) and backend (FastAPI, Flask) through cloud infrastructure design and operations, primarily on AWS.

In July 2026 I joined The Asahi Shimbun Company as a software engineer in the Service Development Department, an in-house, AI-native engineering organization. Previously, as Tech Lead on an AI SaaS engagement for a large manufacturer, I led design and development of a RAG system using LangChain, LangGraph, and MCP. As a freelancer I have also contributed to multiple projects, including mobile apps (Flutter / iOS), web applications, and data platform builds.

I focus on applying AI, shaping architecture, and supporting engineering teams—taking work from PoC through production operations.

Self-introduction

I am a full-stack engineer who can own delivery from frontend and backend through cloud infrastructure and AI agent development. With Python and TypeScript as my core stack and over eight years of experience, I led RAG system design and development as Tech Lead on an AI SaaS engagement, using LangChain, LangGraph, and MCP.

On the technical side, I design and operate infrastructure on AWS (EC2, Lambda, ECS, CDK, and more) and Google Cloud (Cloud Run, GKE), implement frontends with Next.js, AngularJS, and Vue.js, and build backends with FastAPI and Flask. I actively adopt modern AI development tools such as Cursor and Claude Code.

In my work I try to anticipate technical issues by looking at project-wide architecture, not only individual requirements. As Tech Lead, I supported teammates through technical guidance, code review, and design decisions, improving quality and productivity.

I keep learning in AI, blockchain, design, and adjacent areas, and aim to choose the right technologies and deliver end-to-end solutions for business problems.

What I want to do next

Since July 2026 I have been taking on a new challenge as a full-stack engineer at The Asahi Shimbun Company’s Service Development Department, working to connect technology more directly to business decisions rather than treating it as a pure implementation tool.

I also find real meaning in supporting the public-interest mission of a news organization through technology. My immediate focus is to build trust by delivering solidly on the work in front of me while deepening my understanding of the team’s development practices. In parallel, I want to bring my experience as a full-stack engineer and Tech Lead back to the organization—introducing ADRs and standardizing AI-native development practices—to help junior engineers grow more self-sufficient.

Over the mid-to-long term, I want to apply the business perspective I gained through my master’s in business administration to look beyond the Service Development Department at the business as a whole, partnering with editorial, advertising, and sales. Through that collaboration, I want to support a public-interest information platform with technology while directly driving business growth.

On a personal level, I’m drawn to the broader question of how information spreads through society and shapes people’s judgment—the “information environment.” I want to explore high-impact themes such as misinformation surrounding climate change through empirical, data-driven research. That lets me approach the same question of information transmission and impact from two sides: as a practitioner at a news organization and as a researcher.

Skills

Category	Technologies & Tools
Languages	Python (6 yrs), TypeScript (6.5 yrs), Dart, PHP, Ruby
Frameworks	FastAPI, Flask, React.js, Next.js, Vue.js, AngularJS, Laravel, Ruby on Rails, Flutter
AI / LLM	LangChain, LangGraph, LangSmith, MCP, Agent Skill, OpenAI API, Azure OpenAI API
AI Dev Tools	Cursor, Claude Code
AWS (5 yrs)	API Gateway, Bedrock, CDK, CloudFormation, CloudFront, CodeBuild, CodePipeline, EC2, ECS, S3, Lambda, RDS, DynamoDB, Batch, Glue, ECR, EMR, CloudWatch, Athena, SES, SQS
Google Cloud (2 yrs)	Cloud Build, Cloud Pub/Sub, Cloud Run, GKE
RDB	MySQL, PostgreSQL (pgvector)
SaaS / PaaS	CircleCI, Firebase, Firestore, GitHub, GitHub Action
Infra / DevOps	Docker, Terraform, Datadog, Sentry
Protocols	GraphQL, gRPC, REST
ORM / Libraries	SQLAlchemy, Prisma, RSpec
Methodologies	Agile (Scrum), Prototyping, MVC

Work experience (detailed)

Software Engineer, Service Development Department (The Asahi Shimbun Company)

Period	Details
Jul 2026 – present	Employment type: Full-time employee Team: Service Development Department — an in-house, AI-native engineering organization (~29 engineers) Summary: Joined The Asahi Shimbun Company as a software engineer in the Service Development Department, which builds and operates the common CMS platform behind 30+ affiliated media sites and drives a large-scale legacy system replacement. Role (onboarding): ・Ramping up on the department's in-house, AI-native development practices and existing codebase ・Contributing to the common CMS platform initiative supporting 30+ media sites ・Supporting the legacy system replacement effort

Period

Details

Jul 2026 –
present

Employment type: Full-time employee

Team: Service Development Department — an in-house, AI-native engineering organization (~29 engineers)

Summary:
Joined The Asahi Shimbun Company as a software engineer in the Service Development Department, which builds and operates the common CMS platform behind 30+ affiliated media sites and drives a large-scale legacy system replacement.

Role (onboarding):
・Ramping up on the department's in-house, AI-native development practices and existing codebase
・Contributing to the common CMS platform initiative supporting 30+ media sites
・Supporting the legacy system replacement effort

DX acceleration support for a major homebuilder (Adixie Inc.)

Period	Details
Jan 2026 – Jun 2026	Employment type: Full-time employee Team: Engineering: 4 / Total: 6 (partner side) Stakeholders: 1 client company (major homebuilder) Languages & frameworks: ・Python + FastAPI / Streamlit ・TypeScript + Next.js Infrastructure: ・AWS (ECS Fargate, Lambda, S3, CloudWatch) ・IaC: Terraform Protocols: REST Tools: GitHub, Cursor, Claude Code, Docker, Notion Summary: As PM, provided end-to-end DX acceleration support for a major homebuilder's DX division—covering 12+ DX initiatives from planning and MVP development through quantitative impact evaluation and executive decision support. Role: ・Project management: Managed overall progress of initiatives, coordinated with client-side leads and executives, and ran weekly reviews and monthly portfolio check-ins ・MVP development: Led agile MVP builds (dashboards, AI-powered checkers, web apps) with rapid feedback cycles via Teams ・Impact measurement: Designed a KPI-based Before/After evaluation framework using leading indicators (conversion rate, response time, error rate, etc.) ・Operations: Built a sustainable operating model with concurrent initiative caps, monthly portfolio reviews, weekly focus reviews, and bi-weekly consultation slots ・Templates: Created and provided project plan templates, approval checklists, and a management ledger Outcomes: ・Established an end-to-end support structure for 12+ DX initiatives, from planning through impact evaluation ・Standardized the flow from planning → alignment → MVP → quantitative validation → executive decision, turning DX from "built and done" into "measurable and actionable" ・Prioritized high-value initiatives with projected annual impact ranging from tens of millions to billions of yen ・Minimized rework through agile MVP development enabling rapid hypothesis testing and pivots

Period

Details

Jan 2026 –
Jun 2026

Employment type: Full-time employee

Team: Engineering: 4 / Total: 6 (partner side)
Stakeholders: 1 client company (major homebuilder)

Languages & frameworks:
・Python + FastAPI / Streamlit
・TypeScript + Next.js

Infrastructure:
・AWS (ECS Fargate, Lambda, S3, CloudWatch)
・IaC: Terraform
Protocols: REST

Tools: GitHub, Cursor, Claude Code, Docker, Notion

Summary:
As PM, provided end-to-end DX acceleration support for a major homebuilder's DX division—covering 12+ DX initiatives from planning and MVP development through quantitative impact evaluation and executive decision support.

Role:
・Project management: Managed overall progress of initiatives, coordinated with client-side leads and executives, and ran weekly reviews and monthly portfolio check-ins
・MVP development: Led agile MVP builds (dashboards, AI-powered checkers, web apps) with rapid feedback cycles via Teams
・Impact measurement: Designed a KPI-based Before/After evaluation framework using leading indicators (conversion rate, response time, error rate, etc.)
・Operations: Built a sustainable operating model with concurrent initiative caps, monthly portfolio reviews, weekly focus reviews, and bi-weekly consultation slots
・Templates: Created and provided project plan templates, approval checklists, and a management ledger

Outcomes:
・Established an end-to-end support structure for 12+ DX initiatives, from planning through impact evaluation
・Standardized the flow from planning → alignment → MVP → quantitative validation → executive decision, turning DX from "built and done" into "measurable and actionable"
・Prioritized high-value initiatives with projected annual impact ranging from tens of millions to billions of yen
・Minimized rework through agile MVP development enabling rapid hypothesis testing and pivots

Internal DX promotion & integrated platform development (Adixie Inc.)

Period	Details
Sep 2025 – Jun 2026	Employment type: Full-time employee Team: Engineering: 5 / Total: 10 Stakeholders: Internal departments (management, IT, HR, accounting, etc.) Languages & frameworks: ・Frontend: TypeScript + Next.js ・Backend: TypeScript + Node.js (REST) ・ORM: Prisma Infrastructure: ・AWS (ECS Fargate, Aurora Serverless v2, Lambda, API Gateway, ECR, CloudWatch, S3, Amplify) ・IaC: Terraform RDB: PostgreSQL (Aurora Serverless v2) Protocols: REST Tools: GitHub, GitHub Actions, Docker, Cursor, Claude Code, MCP, Prisma, Docusaurus Summary: Led planning, design, and construction of an integrated internal business platform as PM. Built a foundation that integrates infrastructure, shared modules, and multiple business APIs in a monorepo for centralized management and deployment. Role: ・Project management: As PM, led requirements definition, task management, work assignments for developers, and coordination with stakeholders across internal departments ・Architecture design: Designed a monorepo structure and repository architecture to integrate and centrally manage multiple business APIs ・Infrastructure: Drove IaC with Terraform on AWS. Optimized costs with Aurora Serverless v2 zero-scale configuration and built container deployment on ECS Fargate ・CI/CD pipeline: Automated deployments via GitHub Actions with dev / prod environment separation and DB migration automation ・API design: Designed REST-oriented APIs for master data, attendance reconciliation, billing, and payroll integrations ・SaaS integration: Designed data sync engines and adapters for external SaaS ・AI agent platform: Designed and implemented MCP (Model Context Protocol) servers and Agent Skills for cross-functional AI agent capabilities ・Documentation: Built unified specification and API documentation site with Docusaurus Outcomes: ・Designed and built an integrated platform from scratch to consolidate multiple business APIs, driving internal DX ・Optimized infrastructure costs through Terraform IaC and Aurora Serverless v2 zero-scale configuration ・Established automated dev / prod deployment pipeline with GitHub Actions CI/CD ・Built an AI agent platform using MCP / Agent Skills, enabling cross-functional AI utilization

Period

Details

Sep 2025 –
Jun 2026

Employment type: Full-time employee

Team: Engineering: 5 / Total: 10
Stakeholders: Internal departments (management, IT, HR, accounting, etc.)

Languages & frameworks:
・Frontend: TypeScript + Next.js
・Backend: TypeScript + Node.js (REST)
・ORM: Prisma

Infrastructure:
・AWS (ECS Fargate, Aurora Serverless v2, Lambda, API Gateway, ECR, CloudWatch, S3, Amplify)
・IaC: Terraform
RDB: PostgreSQL (Aurora Serverless v2)
Protocols: REST

Tools: GitHub, GitHub Actions, Docker, Cursor, Claude Code, MCP, Prisma, Docusaurus

Summary:
Led planning, design, and construction of an integrated internal business platform as PM. Built a foundation that integrates infrastructure, shared modules, and multiple business APIs in a monorepo for centralized management and deployment.

Role:
・Project management: As PM, led requirements definition, task management, work assignments for developers, and coordination with stakeholders across internal departments
・Architecture design: Designed a monorepo structure and repository architecture to integrate and centrally manage multiple business APIs
・Infrastructure: Drove IaC with Terraform on AWS. Optimized costs with Aurora Serverless v2 zero-scale configuration and built container deployment on ECS Fargate
・CI/CD pipeline: Automated deployments via GitHub Actions with dev / prod environment separation and DB migration automation
・API design: Designed REST-oriented APIs for master data, attendance reconciliation, billing, and payroll integrations
・SaaS integration: Designed data sync engines and adapters for external SaaS
・AI agent platform: Designed and implemented MCP (Model Context Protocol) servers and Agent Skills for cross-functional AI agent capabilities
・Documentation: Built unified specification and API documentation site with Docusaurus

Outcomes:
・Designed and built an integrated platform from scratch to consolidate multiple business APIs, driving internal DX
・Optimized infrastructure costs through Terraform IaC and Aurora Serverless v2 zero-scale configuration
・Established automated dev / prod deployment pipeline with GitHub Actions CI/CD
・Built an AI agent platform using MCP / Agent Skills, enabling cross-functional AI utilization

AI SaaS development for a major manufacturing client (Adixie Inc.)

Period	Details
Mar 2025 – Jun 2026	Employment type: Full-time employee Team: Engineering: 8 / Total: 12 Stakeholders: Several client companies Languages & frameworks: ・Frontend: TypeScript + Next.js ・Backend: Python + FastAPI Infrastructure: AWS, PostgreSQL (pgvector) Protocols: REST Tools: GitHub, Notion, Cursor, MCP (PostgreSQL, etc.), Docker, LangChain, LangGraph, LangSmith, OpenAI API, Azure OpenAI API, Claude Code, SQLAlchemy Summary: Led development of a RAG system over internal and design documents for an AI SaaS engagement targeting large manufacturers, as Tech Lead. Role: ・Architecture: Owned end-to-end design of the RAG stack: FastAPI backend, pipeline from PDF ingestion through embedding and search, and PostgreSQL/pgvector for scalable document search. ・Frontend: Single-handedly implemented core Next.js UI—interactive chat with AI agents and search result visualization—and integration with backend APIs. ・AI agents: Built multi-step reasoning with LangGraph, prompt engineering for manufacturing terminology and context, and validation from ontology level through graph search—delivering hybrid search combining vector, graph, and agents. ・Domain modeling: Designed domain-specific agents and a multi-agent split of work; tuned chunking strategy to balance context retention and retrieval quality. Outcomes: ・Delivered a production-oriented hybrid search system by owning ontology design through accuracy evaluation against real client workflows and terminology. ・Multi-agent design (domain routing, coordination, reflection) enabled complex operational queries that a single agent could not handle. ・Established a continuous prompt-improvement loop so the team could keep raising search quality.

Period

Details

Mar 2025 –
Jun 2026

Employment type: Full-time employee

Team: Engineering: 8 / Total: 12
Stakeholders: Several client companies

Languages & frameworks:
・Frontend: TypeScript + Next.js
・Backend: Python + FastAPI

Infrastructure: AWS, PostgreSQL (pgvector)
Protocols: REST

Tools: GitHub, Notion, Cursor, MCP (PostgreSQL, etc.), Docker, LangChain, LangGraph, LangSmith, OpenAI API, Azure OpenAI API, Claude Code, SQLAlchemy

Summary:
Led development of a RAG system over internal and design documents for an AI SaaS engagement targeting large manufacturers, as Tech Lead.

Role:
・Architecture: Owned end-to-end design of the RAG stack: FastAPI backend, pipeline from PDF ingestion through embedding and search, and PostgreSQL/pgvector for scalable document search.
・Frontend: Single-handedly implemented core Next.js UI—interactive chat with AI agents and search result visualization—and integration with backend APIs.
・AI agents: Built multi-step reasoning with LangGraph, prompt engineering for manufacturing terminology and context, and validation from ontology level through graph search—delivering hybrid search combining vector, graph, and agents.
・Domain modeling: Designed domain-specific agents and a multi-agent split of work; tuned chunking strategy to balance context retention and retrieval quality.

Outcomes:
・Delivered a production-oriented hybrid search system by owning ontology design through accuracy evaluation against real client workflows and terminology.
・Multi-agent design (domain routing, coordination, reflection) enabled complex operational queries that a single agent could not handle.
・Established a continuous prompt-improvement loop so the team could keep raising search quality.

Mobile app for a used-car dealership (Freelance)

Period	Details
Dec 2024 – Feb 2025	Employment type: Freelance (3 months) Team: Engineering: 2 / Total: 4 Stakeholders: 1 client company Languages & frameworks: ・Mobile: Dart + Flutter ・Backend: Python + FastAPI ・Web: TypeScript + Next.js Infrastructure (AWS): API Gateway, EC2, S3, CloudFormation, CDK, Lambda, RDS, ECR, CloudWatch, SQS RDB: MySQL Protocols: REST Tools: GitHub, Backlog, Terraform, Sentry Platform: iOS Summary: Full-stack delivery from Flutter iOS app through greenfield AWS infrastructure for API migration. Role: ・iOS / Flutter: End-to-end design and implementation with direct user feedback, focusing on intuitive UX. ・Infrastructure: Built and operated AWS from scratch for migrated APIs; IaC with CloudFormation and CDK. ・Collaboration: Worked closely with PO, SM, and developers in Scrum. Outcomes: ・Covered mobile development and new AWS infrastructure as part of the Scrum team. ・Enabled new API operations via greenfield AWS services. ・Helped keep the project moving through tight cross-functional collaboration.

Period

Details

Dec 2024 –
Feb 2025

Employment type: Freelance (3 months)

Team: Engineering: 2 / Total: 4
Stakeholders: 1 client company

Languages & frameworks:
・Mobile: Dart + Flutter
・Backend: Python + FastAPI
・Web: TypeScript + Next.js

Infrastructure (AWS): API Gateway, EC2, S3, CloudFormation, CDK, Lambda, RDS, ECR, CloudWatch, SQS
RDB: MySQL
Protocols: REST

Tools: GitHub, Backlog, Terraform, Sentry
Platform: iOS

Summary:
Full-stack delivery from Flutter iOS app through greenfield AWS infrastructure for API migration.

Role:
・iOS / Flutter: End-to-end design and implementation with direct user feedback, focusing on intuitive UX.
・Infrastructure: Built and operated AWS from scratch for migrated APIs; IaC with CloudFormation and CDK.
・Collaboration: Worked closely with PO, SM, and developers in Scrum.

Outcomes:
・Covered mobile development and new AWS infrastructure as part of the Scrum team.
・Enabled new API operations via greenfield AWS services.
・Helped keep the project moving through tight cross-functional collaboration.

Corporate 1-on-1 web application (Freelance)

Period	Details
Mar 1, 2024 – Nov 30, 2024	Employment type: Freelance Team: CTO ×1, Tech lead ×1, Engineers ×8 (10 total) Stakeholders: 1 client company Languages & frameworks: ・Frontend: TypeScript + AngularJS / HTML + SCSS + Tailwind CSS ・Backend: Python + FastAPI / Ruby on Rails Infrastructure: AWS Protocols: REST, GraphQL Tools: GitHub, Sentry, AWS CloudWatch, Notion Summary: Built and maintained a web app supporting corporate 1-on-1 meetings—new features, UI/UX, and ops—as a full-stack engineer. Role: ・Frontend: TypeScript + AngularJS for new features and improvements. ・UI/UX: Tailwind CSS and SCSS for a consistent design system. ・Backend: Primarily Python + FastAPI for new work; Rails for legacy maintenance. ・Operations: CloudWatch for logs, Sentry for errors—fast incident response. Outcomes: ・Improved UX through new features and UI work. ・Reduced effort and increased consistency via the design system. ・Stable operations through combined monitoring. ・Strengthened full-stack ownership from frontend through backend and ops. ・Automation around logs and errors improved efficiency and response time.

Period

Details

Mar 1, 2024 –
Nov 30, 2024

Employment type: Freelance

Team: CTO ×1, Tech lead ×1, Engineers ×8 (10 total)
Stakeholders: 1 client company

Languages & frameworks:
・Frontend: TypeScript + AngularJS / HTML + SCSS + Tailwind CSS
・Backend: Python + FastAPI / Ruby on Rails

Infrastructure: AWS
Protocols: REST, GraphQL

Tools: GitHub, Sentry, AWS CloudWatch, Notion

Summary:
Built and maintained a web app supporting corporate 1-on-1 meetings—new features, UI/UX, and ops—as a full-stack engineer.

Role:
・Frontend: TypeScript + AngularJS for new features and improvements.
・UI/UX: Tailwind CSS and SCSS for a consistent design system.
・Backend: Primarily Python + FastAPI for new work; Rails for legacy maintenance.
・Operations: CloudWatch for logs, Sentry for errors—fast incident response.

Outcomes:
・Improved UX through new features and UI work.
・Reduced effort and increased consistency via the design system.
・Stable operations through combined monitoring.
・Strengthened full-stack ownership from frontend through backend and ops.
・Automation around logs and errors improved efficiency and response time.

Sales-facing AI web app (Freelance)

Period	Details
Jan 2024 – Aug 31, 2024	Employment type: Freelance Team: PM ×1, Engineers ×2 Stakeholders: 1 client company Languages & frameworks: ・Frontend: TypeScript + Next.js ・Backend: Python Infrastructure: Firebase, GCP Protocols: REST Tools: GitHub, Tailwind CSS, LangChain (temperature, agents, etc.), Notion Summary: Application for sales users to generate prompts from product, manufacturer, and customer data—from PoC through production. Role: ・Frontend: TypeScript + Next.js features. ・Backend: Firebase SDK + Python for data handling and prompt generation. ・Prompting: LangChain tuning (temperature, agents) for better outputs. ・Financial data: Extracted data from EDINET (XBRL) and computed metrics (e.g. revenue, operating profit) using accounting knowledge. ・Operations: Owned path from PoC to production. Outcomes: ・Delivered an AI prompt app tailored to sales workflows. ・Improved response quality via LangChain tuning. ・Consistent UI with Tailwind. ・Better accuracy on financial extraction and KPI calculation using EDINET and accounting input. ・Shipped end-to-end in a small team, exceeding client expectations.

Period

Details

Jan 2024 –
Aug 31, 2024

Employment type: Freelance

Team: PM ×1, Engineers ×2
Stakeholders: 1 client company

Languages & frameworks:
・Frontend: TypeScript + Next.js
・Backend: Python

Infrastructure: Firebase, GCP
Protocols: REST

Tools: GitHub, Tailwind CSS, LangChain (temperature, agents, etc.), Notion

Summary:
Application for sales users to generate prompts from product, manufacturer, and customer data—from PoC through production.

Role:
・Frontend: TypeScript + Next.js features.
・Backend: Firebase SDK + Python for data handling and prompt generation.
・Prompting: LangChain tuning (temperature, agents) for better outputs.
・Financial data: Extracted data from EDINET (XBRL) and computed metrics (e.g. revenue, operating profit) using accounting knowledge.
・Operations: Owned path from PoC to production.

Outcomes:
・Delivered an AI prompt app tailored to sales workflows.
・Improved response quality via LangChain tuning.
・Consistent UI with Tailwind.
・Better accuracy on financial extraction and KPI calculation using EDINET and accounting input.
・Shipped end-to-end in a small team, exceeding client expectations.

Manufacturing web application (Freelance)

Period	Details
May 2023 – Feb 28, 2024	Employment type: Freelance Team: Tech leads ×2, Engineers ×10 Stakeholders: 1 client company Languages & frameworks: TypeScript, Nuxt.js 3, Pinia, React.js Infrastructure: AWS Protocols: REST, GraphQL Tools: GitHub, Tailwind CSS, Hasura, Sentry, Datadog, Notion Summary: AI-enabled web app for manufacturing: efficient frontend–backend integration, stability in production, and React rewrite of a legacy app. Role: ・Frontend: TypeScript + Nuxt 3 + Pinia, UX-focused features. ・Rewrite: Migrated legacy UI to React for maintainability and extensibility. ・Styling: Tailwind for consistent, efficient UI. ・Data: Hasura + GraphQL for efficient reads/writes. ・Reliability: Sentry + Datadog from detection through handling. Outcomes: ・Shipped on Nuxt 3 with a modern toolchain. ・Flexible, consistent UI with Tailwind. ・Faster, more flexible data access via Hasura + GraphQL. ・Reduced tech debt and improved maintainability with the React migration. ・Stronger stability and faster troubleshooting with observability. ・Broadened frontend and operations skill set.

Period

Details

May 2023 –
Feb 28, 2024

Employment type: Freelance

Team: Tech leads ×2, Engineers ×10
Stakeholders: 1 client company

Languages & frameworks: TypeScript, Nuxt.js 3, Pinia, React.js

Infrastructure: AWS
Protocols: REST, GraphQL

Tools: GitHub, Tailwind CSS, Hasura, Sentry, Datadog, Notion

Summary:
AI-enabled web app for manufacturing: efficient frontend–backend integration, stability in production, and React rewrite of a legacy app.

Role:
・Frontend: TypeScript + Nuxt 3 + Pinia, UX-focused features.
・Rewrite: Migrated legacy UI to React for maintainability and extensibility.
・Styling: Tailwind for consistent, efficient UI.
・Data: Hasura + GraphQL for efficient reads/writes.
・Reliability: Sentry + Datadog from detection through handling.

Outcomes:
・Shipped on Nuxt 3 with a modern toolchain.
・Flexible, consistent UI with Tailwind.
・Faster, more flexible data access via Hasura + GraphQL.
・Reduced tech debt and improved maintainability with the React migration.
・Stronger stability and faster troubleshooting with observability.
・Broadened frontend and operations skill set.

Traveler-focused B2C web application (Freelance)

Period	Details
Oct 1, 2021 – Dec 31, 2022	Employment type: Freelance Team: PO ×1, Tech lead ×1, Engineers ×3 Stakeholders: 1 client company Languages & frameworks: ・Frontend: TypeScript + Vue.js ・Backend: PHP + Laravel Infrastructure (AWS): CloudFront, CloudWatch, CodePipeline, EC2, S3, CodeBuild, RDS Protocols: REST, GraphQL Tools: GitHub, Pusher, SCSS, Notion Summary: New chat features and enhancements for a B2C travel web app, plus real-time comms and CI/CD. Role: ・Chat (new): TypeScript + Vue.js frontend and UI. ・Backend: Laravel with JWT-based auth. ・CI/CD: CodeBuild + CodePipeline for build, test, deploy. ・Realtime: Pusher across frontend and backend. ・Enhancements: Additional features on an existing education-oriented web product. Outcomes: ・Designed and shipped chat with realtime UX improvements. ・CI/CD improved deploy speed and reliability. ・Stable realtime behavior after research, design, and implementation. ・Full-stack growth across frontend and backend. ・Increased value of the existing product through new capabilities.

Period

Details

Oct 1, 2021 –
Dec 31, 2022

Employment type: Freelance

Team: PO ×1, Tech lead ×1, Engineers ×3
Stakeholders: 1 client company

Languages & frameworks:
・Frontend: TypeScript + Vue.js
・Backend: PHP + Laravel

Infrastructure (AWS): CloudFront, CloudWatch, CodePipeline, EC2, S3, CodeBuild, RDS
Protocols: REST, GraphQL

Tools: GitHub, Pusher, SCSS, Notion

Summary:
New chat features and enhancements for a B2C travel web app, plus real-time comms and CI/CD.

Role:
・Chat (new): TypeScript + Vue.js frontend and UI.
・Backend: Laravel with JWT-based auth.
・CI/CD: CodeBuild + CodePipeline for build, test, deploy.
・Realtime: Pusher across frontend and backend.
・Enhancements: Additional features on an existing education-oriented web product.

Outcomes:
・Designed and shipped chat with realtime UX improvements.
・CI/CD improved deploy speed and reliability.
・Stable realtime behavior after research, design, and implementation.
・Full-stack growth across frontend and backend.
・Increased value of the existing product through new capabilities.

PoC development for new AI-powered applications (IDH Inc.)

Period	Details
Aug 1, 2020 – Sep 30, 2021	Employment type: Full-time employee Team: PM ×1, Lead ×1, Engineers ×5 Stakeholders: 1 client company Languages & frameworks: ・Frontend: TypeScript + Vue.js ・Backend: Python + Flask / FastAPI Infrastructure: MySQL, SQLite Protocols: REST Tools: GitLab, Docker, Pytest Summary: Two PoC applications: ・Money-laundering audit app: TypeScript + Vue.js + Flask ・Speech recognition & captioning app: TypeScript + Vue.js + FastAPI Role: ・Screen and functional design in the design phase. ・Full-stack development with Vue.js and Flask/FastAPI. ・Backend APIs and logic; tests with Pytest. ・Audio/video speech recognition and text output through delivery. Outcomes: ・Delivered two AI PoCs with client handoff. ・Improved backend quality and reliability with Pytest. ・Owned design through implementation, including architecture documentation. ・Efficient frontend–backend integration within a tight timeline.

Period

Details

Aug 1, 2020 –
Sep 30, 2021

Employment type: Full-time employee

Team: PM ×1, Lead ×1, Engineers ×5
Stakeholders: 1 client company

Languages & frameworks:
・Frontend: TypeScript + Vue.js
・Backend: Python + Flask / FastAPI

Infrastructure: MySQL, SQLite
Protocols: REST

Tools: GitLab, Docker, Pytest

Summary:
Two PoC applications:
・Money-laundering audit app: TypeScript + Vue.js + Flask
・Speech recognition & captioning app: TypeScript + Vue.js + FastAPI

Role:
・Screen and functional design in the design phase.
・Full-stack development with Vue.js and Flask/FastAPI.
・Backend APIs and logic; tests with Pytest.
・Audio/video speech recognition and text output through delivery.

Outcomes:
・Delivered two AI PoCs with client handoff.
・Improved backend quality and reliability with Pytest.
・Owned design through implementation, including architecture documentation.
・Efficient frontend–backend integration within a tight timeline.

Mobile app UI development (IDH Inc.)

Period	Details
Jan 1, 2021 – Jul 31, 2021	Employment type: Full-time employee Team: PO ×1, Scrum Masters ×4, Engineers ×12 Stakeholders: 1 client company Languages & frameworks: JavaScript, React.js, Gatsby, Jest, TestCafe Infrastructure: Firebase Realtime Database, GCP (GKE) Protocols: REST Tools: GitLab, Docker, Kubernetes, Jira, nginx Summary: Design, build, and operate a mobile-oriented experience using React and GCP in a cloud-native style. Role: ・Frontend with React.js + Gatsby. ・Design docs and feature design from requirements. ・CI/CD from dev through release. ・Jest unit tests and TestCafe E2E tests. Outcomes: ・Shipped the app on React + GCP on an aggressive timeline. ・CI/CD reduced effort from development to release. ・Tests improved quality. ・Architecture diagrams and requirements docs streamlined design.

Period

Details

Jan 1, 2021 –
Jul 31, 2021

Employment type: Full-time employee

Team: PO ×1, Scrum Masters ×4, Engineers ×12
Stakeholders: 1 client company

Languages & frameworks: JavaScript, React.js, Gatsby, Jest, TestCafe

Infrastructure: Firebase Realtime Database, GCP (GKE)
Protocols: REST

Tools: GitLab, Docker, Kubernetes, Jira, nginx

Summary:
Design, build, and operate a mobile-oriented experience using React and GCP in a cloud-native style.

Role:
・Frontend with React.js + Gatsby.
・Design docs and feature design from requirements.
・CI/CD from dev through release.
・Jest unit tests and TestCafe E2E tests.

Outcomes:
・Shipped the app on React + GCP on an aggressive timeline.
・CI/CD reduced effort from development to release.
・Tests improved quality.
・Architecture diagrams and requirements docs streamlined design.

Data platform construction (IDH Inc.)

Period	Details
Mar 1, 2019 – Dec 31, 2020	Employment type: Full-time employee Team: PO ×1, Scrum Master ×1, Tech lead ×1, Engineers ×6 Stakeholders: 1 client company Languages & frameworks: Python, Pytest, Boto3 Infrastructure (AWS): EC2, S3, Lambda, RDS, DynamoDB, Batch, Glue, ECR, EMR, CloudWatch, Athena Protocols: REST Tools: GitHub, Jira, Presto, Docker Summary: Built an analytics platform to process and aggregate large-scale game telemetry for analysis—ETL development and operations. Role: ・Python applications for design, new development, operations, and maintenance. ・Unit tests with Pytest. ・Backend automation against AWS with Boto3. ・Used EC2, S3, Lambda, RDS, DynamoDB, Batch, Glue, and related services for the data platform. Team context: ・Scrum with rapid feature delivery and fixes. ・Very large data volumes required cost-performance tuning and scalable design. ・Operations needed quick incident response and new requirements. Outcomes: ・Data pipelines processed large volumes more efficiently than before. ・Tests improved quality and sped up fixes. ・AWS design choices improved cost-performance. ・Flexible delivery on new requirements built client trust.

Period

Details

Mar 1, 2019 –
Dec 31, 2020

Employment type: Full-time employee

Team: PO ×1, Scrum Master ×1, Tech lead ×1, Engineers ×6
Stakeholders: 1 client company

Languages & frameworks: Python, Pytest, Boto3

Infrastructure (AWS): EC2, S3, Lambda, RDS, DynamoDB, Batch, Glue, ECR, EMR, CloudWatch, Athena
Protocols: REST

Tools: GitHub, Jira, Presto, Docker

Summary:
Built an analytics platform to process and aggregate large-scale game telemetry for analysis—ETL development and operations.

Role:
・Python applications for design, new development, operations, and maintenance.
・Unit tests with Pytest.
・Backend automation against AWS with Boto3.
・Used EC2, S3, Lambda, RDS, DynamoDB, Batch, Glue, and related services for the data platform.

Team context:
・Scrum with rapid feature delivery and fixes.
・Very large data volumes required cost-performance tuning and scalable design.
・Operations needed quick incident response and new requirements.

Outcomes:
・Data pipelines processed large volumes more efficiently than before.
・Tests improved quality and sped up fixes.
・AWS design choices improved cost-performance.
・Flexible delivery on new requirements built client trust.

B2C investment application (TecoTec Inc.)

Period	Details
Sep 1, 2018 – Feb 28, 2019	Employment type: Full-time employee Team: PM ×1, Engineers ×4 Stakeholders: 1 client company Languages & frameworks: Python Infrastructure (AWS): Lambda, S3, RDS Protocols: REST Tools: GitLab, Jupyter Notebook, Redmine Summary: Collected, analyzed, and visualized user investment data; generated individualized performance and market trend reports. Role: ・End-to-end flow from ingestion through analysis, visualization, and delivery. ・Analysis in Python with numpy/pandas. ・Charts and reports with matplotlib/seaborn. ・REST APIs for processed results. ・Automated, customized user reports. Outcomes: ・Reporting improved satisfaction by surfacing performance clearly. ・Python workflows shortened development time. ・APIs enabled timely data and higher product value. ・Visualization strengthened trust and insight for the client.

Period

Details

Sep 1, 2018 –
Feb 28, 2019

Employment type: Full-time employee

Team: PM ×1, Engineers ×4
Stakeholders: 1 client company

Languages & frameworks: Python

Infrastructure (AWS): Lambda, S3, RDS
Protocols: REST

Tools: GitLab, Jupyter Notebook, Redmine

Summary:
Collected, analyzed, and visualized user investment data; generated individualized performance and market trend reports.

Role:
・End-to-end flow from ingestion through analysis, visualization, and delivery.
・Analysis in Python with numpy/pandas.
・Charts and reports with matplotlib/seaborn.
・REST APIs for processed results.
・Automated, customized user reports.

Outcomes:
・Reporting improved satisfaction by surfacing performance clearly.
・Python workflows shortened development time.
・APIs enabled timely data and higher product value.
・Visualization strengthened trust and insight for the client.

Credit card credit-management support (FUJISOFT Inc.)

Period	Details
Jun 1, 2018 – Jul 31, 2018	Employment type: Full-time employee Team: PM ×1, Engineers ×3 (4 total) Stakeholders: 1 client company Languages & frameworks: VBA Infrastructure: N/A Protocols: N/A Tools: Excel Summary: Supported credit operations: requirements-phase assistance, efficiency tooling, documentation, and project support. Role: ・Requirements support: Organized and managed related documents. ・Efficiency tools: VBA tools for PM workflows and document automation. ・Reporting: Data aggregation, materials, and progress tracking. Outcomes: ・Smoother requirements phase through structured documentation. ・Faster daily PM work via VBA tooling. ・Better visibility and sharing through materials and progress tracking. ・Foundational knowledge of credit operations and the value of documentation and tooling.

Period

Details

Jun 1, 2018 –
Jul 31, 2018

Employment type: Full-time employee

Team: PM ×1, Engineers ×3 (4 total)
Stakeholders: 1 client company

Languages & frameworks: VBA

Infrastructure: N/A
Protocols: N/A

Tools: Excel

Summary:
Supported credit operations: requirements-phase assistance, efficiency tooling, documentation, and project support.

Role:
・Requirements support: Organized and managed related documents.
・Efficiency tools: VBA tools for PM workflows and document automation.
・Reporting: Data aggregation, materials, and progress tracking.

Outcomes:
・Smoother requirements phase through structured documentation.
・Faster daily PM work via VBA tooling.
・Better visibility and sharing through materials and progress tracking.
・Foundational knowledge of credit operations and the value of documentation and tooling.

Hobbies

Reading (about 300–400 books per year)
Music (on the order of 1,500 tracks listened to in 2025)
Travel (47 prefectures in Japan; 32 countries/regions)
Shogi (~2-dan level)
Language learning (English, Chinese, Spanish)
Dance (hip-hop, K-pop, house, popping)
Running
Violin
Acoustic guitar
Saxophone
Visiting museums and art galleries

Resume — Yasuo Nonaka

Full-stack engineer, Tokyo — English resume.

Resume

Basic Information

Professional summary

Self-introduction

What I want to do next

Skills

Work experience (detailed)

Software Engineer, Service Development Department (The Asahi Shimbun Company)

DX acceleration support for a major homebuilder (Adixie Inc.)

Internal DX promotion & integrated platform development (Adixie Inc.)

AI SaaS development for a major manufacturing client (Adixie Inc.)

Mobile app for a used-car dealership (Freelance)

Corporate 1-on-1 web application (Freelance)

Sales-facing AI web app (Freelance)

Manufacturing web application (Freelance)

Traveler-focused B2C web application (Freelance)

PoC development for new AI-powered applications (IDH Inc.)

Mobile app UI development (IDH Inc.)

Data platform construction (IDH Inc.)

B2C investment application (TecoTec Inc.)

Credit card credit-management support (FUJISOFT Inc.)

Hobbies