AI Architect (Telecom Background)

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.