2025年の振り返り & 新しい仲間の募集

Job Title: Senior Software Engineer (AI)Employment Type: PermanentWork Location: Remote About CloudBeesCloudBees enables enterprises to deliver scalable, compliant, and secure software, empowering developers to do their best work. Seamlessly integrating into any hybrid and heterogeneous environment, CloudBees is more than a tool—it's a strategic partner in your cloud transformation journey, ensuring security, compliance, and operational efficiency while enhancing the developer experience across your entire software development lifecycle. It allows developers to bring and execute their code anywhere, providing greater flexibility and freedom through fast, self-serve, and secure workflows.CloudBees supports organizations at every step of their DevSecOps journey, whether using Jenkins on-premise or transitioning software delivery to the cloud. We’re helping customers build the future, today.About the RoleThis is a truly unique opportunity in which, as a senior software engineer at CloudBees, you will be the kernel of the expanding AI team, and play an instrumental role in laying out the foundation of a new SaaS product powered by data and AI. You will be a part of a US tech startup with a global team & customer reach, which provides an excellent career growth opportunity. We are looking for a pioneer who is excited to pick up new exciting technologies, experiment, learn, and chart unknown territories.Key ResponsibilitiesDevelop code, infrastructure, data processing and work on ML algorithmsOperate a service and be accountable to its business impactWork closely with prospects and customers to resolve problems they are experiencing & make them happyQualificationsRequired:Bachelor's degree in Computer Science or a related technical fieldExperience programming in Java/GoLang/Python (>2 years). Experience developing web applicationsExcellent problem solving and communication skillsAbility to be self sufficient given the proper guidanceSelf-motivated and driven personalityFully proficient in English written and spoken languageComfortable working closely with support, customers and community to help resolve issuesPassion for teams: building, working in them, encouraging team members to reach their potentialPreferred (not mandatory):Data processing experienceMachine Learning experienceGo / Python experienceExperience working in Agile methodologiesWorking ConditionsStandard working hours: 9am - 6pm., Mon–Fri, or as per business needsWork location / travel expectations: RemoteReasonable accommodations will be considered in line with the Rights of Persons with Disabilities Act, 2016.Compensation & BenefitsBenefits offered: health insurance, provident fund, paid leave, remote allowance.5% Variable BonusEqual Opportunity StatementCloudBees is an Equal Opportunity Employer. We do not discriminate on the basis of caste, religion, color, gender, sexual orientation, age, marital status, disability, or any other status protected under applicable law. We are committed to creating an inclusive workplace where everyone can thrive.Data Protection StatementAll personal information collected during the recruitment process will be handled in accordance with applicable Indian data protection laws and Cloudbees privacy policy.DisclaimerThis job description is intended to provide a summary of the position and its responsibilities. It is not an exhaustive list of duties. Responsibilities and activities may evolve as per organisational requirements.

ある日セールスから、とあるエンタープライズ企業のトライアルが始まることを知らされました。嬉しい知らせでしたが、詳細を聞いてみると対象のテナントは従来のテナントと比べて50倍以上のデータ規模であるということが判明します。 ISUCONのように既存リソースを極限まで最適化し、解決することが理想です。しかし実際の運用では、「サービスを止められない」、 「データの欠損は許されない」 など運用上の制約があり難しい場合があります。 一方でスケールアップやリソースの追加といった、お金をかけて解決する選択も実際の運用中では有効なオプションとなり得ます。 また、スピードを優先することで長期的には技術的負債になり得そうな選択肢を取ることも出てきます。 本発表では、アプリケーション、バッチジョブ、インフラ に渡って トライアルから本契約に至る過程で直面した"急"な大規模データリクエストにおいて、どのような対策を事前にとったのか、どのような問題が起こったのか、どのように解決していったのかを紹介します。 この発表を通じて、制約下でどうスケールアップ/リソース追加を選択し改善を重ねたかを共有し、急な要求に直面した際の一つの参考事例になればと思います。 ## アジェンダ (予定) - サービスおよびシステムについての紹介 - あらまし - 課題の洗い出し - システムを止めないといけない対応 - システムを止めなくてもできる対応 - 実際の対応例 - DBのスケールアップ - kubernetesのserviceの分離 - PostgreSQLのJSONBサイズの限界と対応 - BigQueryは1行あたり１GBまで - など - 振り返り および 今後 - まとめ