RIC Solution Architect, Network Insight Engineering Department (RMI Cognitive Customer Experience Management Div )
Rakuten Crimson House
Rakuten Mobile
Job Description:
About Organization
We are the Network Insight Engineering team in Cognitive Customer Experience Management Division, dedicated to leveraging cutting-edge AI/ML and data science techniques to harness the power of Telecom big data. Our mission is to drive innovation that optimizes network performance and autonomously enhance customer experience. Join us and be part of a dynamic team that is at the forefront of technological advancements in the telecommunications industry.
We are seeking an experienced RIC Solution Architect to join our team in Tokyo. This role involves designing, developing, and implementing Radio Intelligent Controller (RIC) solutions within an Open RAN (O-RAN) environment. The successful candidate will collaborate with a global team , working closely with cross-functional teams to enhance network performance and enable advanced use cases leveraging AI/ML. This is an exciting opportunity to work with cutting-edge technologies and be part of a forward-thinking organization.
Job Duties
Architect and design RIC solutions in accordance with O-RAN Alliance standards and specifications.
Involve in the development of xApps and rApps for both Near-Real-Time RIC and Non-Real-Time RIC to optimize network performance.
Collaborate with cross-functional teams, including network engineering, software development, and data science, to define RIC requirements and use cases.
Ensure seamless integration and interoperability of RIC with other RAN components in an end-to-end fully virtualized cloud-native mobile network.
Lead proof-of-concept (PoC) and pilot projects to validate RIC functionalities in live network environments.
Utilize AI/ML models for RAN optimization tasks, including interference management, load balancing, and energy efficiency.
Conduct network performance analysis to provide actionable insights and support network optimization.
Work with vendors and partners to evaluate and integrate third-party xApps/rApps into the RIC ecosystem.
Stay current with industry trends, O-RAN, and emerging technologies related to RIC.
Document technical designs, requirements, and deployment strategies for RIC solutions.
Provide technical leadership and mentoring to junior engineers and architects within team.
Minimum Qualifications
Bachelor’s or Master’s degree in Telecommunications, Electrical Engineering, Computer Science, or a related field.
Over 8 years of experience in the telecommunications industry, with at least 3 years focusing on RAN architecture, RIC, or O-RAN.
Deep understanding of O-RAN architecture, RIC framework (Near-RT RIC, Non-RT RIC), and associated interfaces (E2, A1, R1).
Proven experience in designing and deploying RIC solutions, including the development of xApps and rApps.
Strong knowledge of 4G/5G RAN, networking protocols (e.g., LTE, NR, NG-RAN), and network functions (e.g., gNB, CU/DU).
Experience with cloud-native technologies (e.g., Kubernetes, Docker, microservices) and their application in telecommunications.
Strong programming skills in languages such as Python, C++, or Golang.
Knowledge of APIs, CNFs, SDN/NFV, and network automation tools.
Excellent problem-solving abilities and a collaborative mindset.
Strong communication and presentation skills, capable of explaining complex technical concepts to non-technical stakeholders.
Preferred Qualifications
Experience with Open RAN solutions and ecosystems.
Familiarity with RAN network planning and optimization tools.
Certifications in O-RAN or related domains.
Hands-on experience with AI/ML frameworks (e.g., PyTorch) for network optimization.
Fluency in both Japanese and English is preferred.
Languages:
English (Overall - 3 - Advanced), Japanese (Overall - 1 - Beginner)* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Architecture Big Data Computer Science CX Docker Engineering Golang Kubernetes Machine Learning Microservices ML models Python PyTorch
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