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AI Solution Architect (RMI Architecture & Business Solutioning Dep) @ Rakuten

JPOnsiteFull-time
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About this role

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)

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