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OXIO · 7 hours ago

Staff Telecom BSS Architect

United States

Full-time

Remote

Lead/Staff

10+ years exp

OXIO is the world’s first telecom-as-a-service (TaaS) platform, democratizing telecom for brands and enterprises. The Staff Telecom BSS Architect will design, implement, and optimize critical business systems, focusing on integrating AI layers into legacy systems for real-time decision-making.

Cloud Data ServicesInfrastructureTelecommunicationsWireless

Diversity & Inclusion

Responsibilities

BSS Core Management: Lead the design and delivery of BSS initiatives for real time rating & charging, billing and back office revenue management

AI Integration & Development: Develop and deploy Generative AI models and Retrieval-Augmented Generation (RAG) systems to automate complex tasks like product configuration, ordering and billing support workflows

Intelligent Automation: Build and maintain autonomous AI agents to manage multi-step processes such as automated service activation and real-time fraud detection

Data & Predictive Analytics: Analyze massive datasets to extract insights for predictive churn analysis, dynamic pricing, and proactive billing alerts

System Optimization: Continuously refine AI models based on evolving telecom data inputs to minimize revenue leakage and reduce operational costs

Collaboration: Work with cross-functional teams to align AI-driven BSS solutions with broader business objectives and ethical AI standards

Qualification

Telecom BSS ExpertiseAI & ML DevelopmentData EngineeringCloud & DevOps4G/5G ArchitecturePythonTypeScriptSQLKubernetesAWS/Azure

Required

10+ years of core Telecom BSS Expertise: Hands-on experience with telecom platforms (e.g., Amdocs, Ericsson, MATRIXX) and a strong understanding of 4G/5G architecture and 3GPP protocols

AI & ML Development: Proficiency in Python or TypeScript for building AI workflows

Experience with LLM APIs and orchestration frameworks

Knowledge of vector databases for context engineering and RAG systems

Data Engineering: Proficiency in SQL and data processing tools to help manage the data foundation required for AI readiness

Cloud & DevOps: Familiarity with cloud-native architectures (Kubernetes, AWS/Azure) and MLOps for deploying and monitoring models in live environments

Education: Bachelor's or Master's degree in Computer Science, Telecommunications Engineering, or a related field