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AI Architect

TalentOS AI LLCBellevue, WA🇺🇸United StatesPosted Oct 13, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Bellevue, WA, United States
Posted
20 hours ago
MicroservicesMLOpsSnowflakeAzureDatabricksStakeholder Management

Job Description

Job Description:

 

  • Telecom Network Expertise - Strong understanding of RAN, Core, Transport, OSS/BSS, Service Assurance, Network Operations, and Engineering domains.
  • AI & Agentic AI Architecture - Expertise in LLMs, RAG, Knowledge Graphs, Vector Databases, Multi-Agent Systems, and AI orchestration frameworks.
  • Network Operations Intelligence - Experience building AI solutions for incident management, RCA, anomaly detection, predictive maintenance, and operational automation.
  • Data & Cloud Architecture - Expertise in Azure, Fabric, Databricks, Snowflake, Data Engineering, MLOps, LLMOps, APIs, and microservices.
  • Knowledge Management Platforms - Experience with semantic search, engineering copilots, enterprise knowledge repositories, and decision-support systems.
  • Enterprise Architecture & Governance - Define architecture standards, integration patterns, security controls, and AI governance frameworks.
  • Leadership & Stakeholder Management - Lead cross-functional teams, mentor engineers, and drive AI adoption across the enterprise.
  • AI Product Innovation & Pre-Sales - Build AI accelerators, support solutioning, proposals, executive engagements, and client workshops.

 

Required Skills & Experience

 

  • Design AI-powered assistants, copilots, and agents to improve knowledge discovery, troubleshooting, and engineering productivity.
  • Lead development of AI products, accelerators, and PoCs addressing business and operational challenges.
  • Build intelligent solutions for incident triage, RCA, predictive insights, automated recommendations, and workflow orchestration.
  • Lead and mentor AI engineers, data scientists, data engineers, software engineers, and domain experts.
  • Integrate structured and unstructured data, telemetry, documentation, and operational knowledge into unified AI platforms.
  • Establish AI architecture, governance, security, observability, and responsible AI standards.
  • Support solutioning, bids, proposals, client presentations, executive briefings, and AI transformation initiatives through technical leadership.

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