AI Architect

The AI Architect designs and implements scalable AI solutions aligned with business objectives. This role defines AI architecture, evaluates machine learning and generative AI technologies, oversees model integration and deployment, and ensures solutions meet performance, security, scalability, and governance requirements. The AI Architect collaborates with data scientists, software engineers, cloud teams, and business stakeholders to deliver reliable AI-driven applications.

• 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.

Education:

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Master's degree in AI, Machine Learning, or Computer Science preferred.
• 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.