5-7 years of experience in telecom network operations and engineering.
Deep knowledge of RAN, Core, Transport, OSS/BSS, and Service Assurance.
Proficiency in AI technologies including LLMs, Knowledge Graphs, and Multi-Agent Systems.
Experience in building AI solutions for incident management and predictive maintenance.
Strong background in data and cloud architecture, particularly with Azure and Databricks.
Familiarity with knowledge management platforms and semantic search technologies.
Demonstrated leadership in cross-functional team environments.
Responsibilities
Design AI-powered assistants to enhance knowledge discovery and engineering productivity.
Lead the development of AI products and proof-of-concepts to solve business challenges.
Build intelligent solutions for incident triage and automated recommendations.
Mentor and guide AI engineers, data scientists, and software engineers.
Integrate diverse data sources into cohesive AI platforms.
Establish AI architecture and governance standards for security and observability.
Support technical leadership in solution design and client engagements.
Benefits
Opportunities for professional development and mentorship.
Access to cutting-edge AI technologies and tools.
Collaborative work environment with cross-functional teams.
Involvement in innovative AI product development.
Engagement in high-impact projects that drive business transformation.
Full Job Description
Key Responsibilities:
Design AI-powered assistants, copilots, and agents to improve knowledge discovery, troubleshooting, and engineering productivity.
Lead the development of AI products, accelerators, and proof-of-concepts (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 solution design, bids, proposals, client presentations, executive briefings, and AI transformation initiatives through technical leadership.
Required Skills and Expertise: Telecom Network Expertise:
Strong understanding of RAN, Core, Transport, OSS/BSS, Service Assurance, Network Operations, and Engineering domains.
AI and Agentic AI Architecture:
Expertise in LLMs, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Vector Databases, Multi-Agent Systems, and AI orchestration frameworks.
Network Operations Intelligence:
Experience building AI solutions for incident management, root cause analysis (RCA), anomaly detection, predictive maintenance, and operational automation.
Data and 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 and Governance:
Define architecture standards, integration patterns, security controls, and AI governance frameworks.
Leadership and Stakeholder Management:
Lead cross-functional teams, mentor engineers, and drive enterprise-wide AI adoption.
AI Product Innovation and Pre-Sales:
Develop AI accelerators and support solution design, proposals, executive engagements, and client workshops.
