AI Solution Architect (RMI Architecture & Business Solutioning Dep)
rakuten · Tokyo, Japan ·
- Category
- Architecture
- Experience
- 3+ years
rakuten · Tokyo, Japan ·
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Design and govern AI systems for a cloud-native mobile network, including proprietary LLM fine-tuning, RAG pipelines, and AI governance frameworks to automate design reviews and ensure network stability.
Job Description:
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.
We are currently spearheading two major initiatives:
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.
Minimum Qualifications
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.
Preferred Qualifications
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.
Languages:
English (Overall - 3 - Advanced)emagine · London, United Kingdom