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AI Solution Architect

楽天モバイル株式会社

テック 東京都 企業サイト 掲載 9/5

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
東京都
雇用形態
記載なし
働き方
記載なし
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

Rakuten MobileのArchitecture Review Boardで、AI/MLのアーキテクチャ設計・評価と、ネットワーク全体のAIガバナンスを担うポジションです。Tech SLMの構築、モデルやAI/MLインフラの評価、設計パターンや監視フレームワークの整備を行います。

応募資格

必須

  • Bachelor’s degree in Computer Science, AI, Machine Learning, Data Science, Telecommunications Engineering, or a related field.
  • 7+ years of total industry experience.
  • 3+ years of experience in application/software design and architecture with AI/ML, including hands-on Generative AI implementation and model design.
  • Strong expertise in LLMs/SLMs, fine-tuning techniques, RAG, vector databases, and prompt engineering.
  • Experience designing and deploying scalable AI solutions using Python, cloud platforms, and Kubernetes.
  • Solid understanding of AI governance, responsible AI practices, security, and data privacy.
  • Basic understanding of Telco networks, Cloud, and networking technologies.
  • Proficiency in English.

歓迎

  • Master’s degree in Computer Science, Data Science, or AI/ML fields.
  • 7–15 years of total experience, with at least 3 years in AI/ML design and implementation.
  • Experience in telecommunications, mobile network architecture, autonomous networks, and related AI use cases.
  • Hands-on expertise with advanced LLM optimization (LoRA, QLoRA, model distillation) and agentic AI frameworks.
  • Experience building enterprise AI platforms, AI copilots, or domain-specific language models.
  • Strong knowledge of MLOps, AI observability, model monitoring, and lifecycle management tools.
  • Proven ability to establish AI governance frameworks and assess third-party AI vendors.
  • Relevant certifications (AWS, Azure, GCP, NVIDIA, or equivalent).
  • Japanese language skills are an additional advantage.

募集要項最終確認 9/25

職種
AIエンジニア
雇用形態
記載なし
給与
記載なし
勤務地
Tokyo, Japan
働き方
記載なし
経験年数
3年以上
学歴
大学卒業以上
掲載日
2026/09/05 13:10(24日前)
最終確認
2026/09/25 20:07(4日前)

仕事内容

About Organization

The Architecture Review Board (ARB) acts as the final technical gatekeeper for every High-Level Design (HLD) within the Rakuten Mobile network. Our mission transcends basic technical feasibility; we analyze solutions through a multi-angle lens, including strategic necessity, security, infrastructure optimization, and competitive benchmarking.

Tech SLM: A proprietary, AI-powered platform utilizing advanced LLM fine-tuning and high-precision RAG pipelines to automate design reviews and knowledge management.

AI Council: A dedicated authority established to enforce audit frameworks, standardized design patterns, and cross-functional synergy for AI use cases across Rakuten Mobile. The ARB serves as a major stakeholder alongside Security and AIDD teams to ensure network stability and integrity.

Why Join Us

Ultimate Tech Authority: Define blueprints, safety guidelines, and architectural guardrails for an entire cloud-native mobile network.

Build Proprietary AI Assets: Go beyond basic APIs; fine-tune foundation models on massive, specialized telecom datasets.

Solve RAG at Scale: Design high-precision, low-latency semantic search systems to eliminate hallucinations in complex network documentation.

High-Impact Ownership: Prevent vendor lock-in and secure network stability while driving the transition toward an autonomous, AI-driven network.

Job Duties

Tech SLM Engineering: Build the proprietary Tech SLM platform using advanced LLM fine-tuning and high-precision RAG pipelines to automate HLD creation and design reviews.

Strategic AI Governance: Serve on the AI Council to validate use cases, set standardized design patterns, and enforce network-wide architectural guardrails.

Algorithmic & Model Assessment: Evaluate open-source or proprietary models against strict telecom network performance, safety, and latency metrics.

ML Infrastructure Review: Audit and review existing AI/ML infrastructure to provide design optimizations that streamline workloads and significantly reduce infrastructure usage.

Vendor Auditing & Integration: Scrutinize third-party AI tools and agentic frameworks to ensure secure integration while preventing vendor lock-in.

Architectural Guardrails: Define standardized architectural disciplines, design patterns, and best practices for AI/ML implementation across the network.

Operational Integrity: Establish comprehensive monitoring frameworks to track model performance, safety, and data governance.

Ecosystem Integration: Ensure seamless, secure, and low-latency integration of AI services within the existing Rakuten Mobile network stack.

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