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Software Engineer - Experimentation System

株式会社メルカリ

テック 記載なし 企業サイト 掲載 9/2

給与

記載なし※ 募集要項に金額の記載がありません

勤務地
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雇用形態
正社員
働き方
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年間休日
記載なし

要約求人票をもとにAIがまとめたものです

This role is responsible for the Experimentation Platform and Feature Flags systems across production and development, including their administration, operation, and optimization. The work includes improving access control, resource allocation, cost optimization, and usability; maintaining a scalable distributed system; scaling the product to handle 10x load; and designing and implementing Agentic Workflows.

応募資格

必須

  • Go, Python, Typescript
  • Good CS fundamental
  • Experience with Cloud technologies
  • communicate effectively with technical and non-technical stake-holders
  • Ability to quickly acquire a solid foundation in Software Engineering concepts such as Domain Driven Design, Event Sourcing, Service Oriented Architecture
  • Ability to design and maintain a scalable distributed system
  • Operate and debug via observability metrics and kubernetes
  • Basic familiarity with cloud based databases and tools (Google Cloud, BigQuery, Redis, etc)
  • Understanding of stateless API design and protocols (gRPC)
  • Define, implement, test, and deploy core features in an existing code base independently
  • English: B2 and above

歓迎

  • Bazel, Cuelang, Terraform, GCP, Kubernetes
  • Implementing parsers and virtual machines
  • Memory allocation optimization

求める人物像

  • Passionate about building tools for developers, with a strong ability to collaborate with the team to identify and implement features.

応募について

  • Japanese: A2 (optional)

使用ツール

BigQueryRedisgRPC

募集要項最終確認 9/26

職種
バックエンドエンジニア
雇用形態
Employment Status: Full-time
給与
記載なし
勤務地
Roppongi
働き方
記載なし
勤務時間
Work Hours: Full Flextime (no core time)
選考の流れ
Recruiting cycle at Mercari Group* Application screening* Skill assessment: For engineering positions, you will be asked to complete a skill assessment on HackerRank or GitHub. For non-engineering positions, you may be asked to complete an assessment depending on the position. (The timing of the assessment may coincide with the interview process.)* Interview: The number of interviews may vary depending on the position.* Reference check: We will ask for online references around the timing of the final interview.* Offer: Offers will be determined carefully in consideration of the final interview and the reference check.
掲載日
2026/09/02 18:21(27日前)
最終確認
2026/09/26 01:59(3日前)

仕事内容

Organization/Team Mission

In the Strategic Experimentation & Analytics (SEA) team, we are responsible for the administration, operation, and optimization of the Experimentation Platform, a system that enables anyone at Mercari to perform A/B tests and experiments and safely and gradually roll out new features.

The team oversees the Experimentation Platform and Feature Flags systems across prod and dev, handling incident response, demos, and roadmap planning while coordinating A/B testing and feature rollouts.

Everyone can learn and acquire empirical knowledge about customer behavior and our service domain

Anyone at Mercari can run experiments at scale

Everyone can understand and trust reproducible experiments

All product changes can be rolled out or rolled back quickly and safely via Feature Flags

Work Responsibilities

Continuously improve the system for access control, resource allocation, cost optimization, and usability to deliver sustained value to engineering and product teams.

Design and maintain a scalable distributed system

Implement new features on an existing code base

Scale the current product to handle 10x load

Design and Implement Agentic Workflows

Unique Challenges

Architecting for modern AI Workflows. As the organization transitions to becoming AI-native, you will be instrumental in designing and building the systems that highly efficiently support new use cases, such as automated configuration, control and data utilization via AI agents.

This role is responsible for ensuring the delivery of a highly cost-effective data analytics environment. The successful candidate will build and maintain a mechanism that naturally fosters cost-awareness among users, eliminates operational waste, and ensures that finite computing resources are precisely allocated to high-priority business tasks.

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