AI Architect (Telecom Background) in Bellevue

Job Description

Job Description:

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• Telecom Network Expertise - Strong understanding of RAN, Core, Transport, OSS/BSS, Service Assurance, Network Operations, and Engineering domains.

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• AI & Agentic AI Architecture - Expertise in LLMs, RAG, Knowledge Graphs, Vector Databases, Multi-Agent Systems, and AI orchestration frameworks.

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• Network Operations Intelligence - Experience building AI solutions for incident management, RCA, anomaly detection, predictive maintenance, and operational automation.

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• Data & Cloud Architecture - Expertise in Azure, Fabric, Databricks, Snowflake, Data Engineering, MLOps, LLMOps, APIs, and microservices.

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• Knowledge Management Platforms - Experience with semantic search, engineering copilots, enterprise knowledge repositories, and decision-support systems.

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• Enterprise Architecture & Governance - Define architecture standards, integration patterns, security controls, and AI governance frameworks.

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• Leadership & Stakeholder Management - Lead cross-functional teams, mentor engineers, and drive AI adoption across the enterprise.

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• AI Product Innovation & Pre-Sales - Build AI accelerators, support solutioning, proposals, executive engagements, and client workshops.

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Required Skills & Experience

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• Design AI-powered assistants, copilots, and agents to improve knowledge discovery, troubleshooting, and engineering productivity.

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• Lead development of AI products, accelerators, and PoCs addressing business and operational challenges.

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• Build intelligent solutions for incident triage, RCA, predictive insights, automated recommendations, and workflow orchestration.

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• Lead and mentor AI engineers, data scientists, data engineers, software engineers, and domain experts.

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• Integrate structured and unstructured data, telemetry, documentation, and operational knowledge into unified AI platforms.

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• Establish AI architecture, governance, security, observability, and responsible AI standards.

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• Support solutioning, bids, proposals, client presentations, executive briefings, and AI transformation initiatives through technical leadership.

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