AI/ML Data Architect
About the role
Architect AI-Ready Data Platforms: Design and implement robust, scalable data architectures powering AI automation, advanced analytics, and agent-based decision systems, specifically for the Telecom sector (OSS/BSS, network operations, customer engagement).
LLM & AI Agent Solutions: Lead architecture and governance of Large Language Model (LLM) and AI agent solutions, including Retrieval-Augmented Generation (RAG), for automation, diagnostics, and workflow orchestration.
Large-Scale Data Systems: Design and build high-volume, cloud-native data platforms capable of processing diverse telecom data (CDRs, telemetry, logs, KPIs, etc.), utilizing patterns like Lakehouse, Data Mesh, and Streaming-first.
End-to-End Data Pipelines: Oversee the creation and operation of end-to-end data pipelines (ingestion through serving), ensuring AI-readiness for LLM training/inference and agent context, with reliability and CI/CD deployment.
Telecom Domain Enablement: Collaborate with telecom business and engineering teams to translate domain-specific use cases into scalable AI/ML data solutions (e.g., network anomaly detection, NOC automation, customer analytics, fraud detection).
Governance, Security & Compliance: Define and enforce data governance, lineage, metadata management, and access control, ensuring secure and compliant use of AI and data according to regulations.
Technical Leadership: Serve as a domain expert and solution authority, defining architectural standards and reference models, mentoring teams, and contributing to enterprise AI/data roadmaps.
Requirements
- 20+ years in IT
- 12+ years in data engineering/architecture
- 5+ years in Telecom domain
- Proven experience with LLM-based/AI-driven data platforms
Skills
- Deep hands-on skills with LLMs, RAG, AI agent orchestration
- Python/Java coding
- Large-scale batch/streaming data systems
- ML/feature engineering pipelines
- Advanced SQL/data modeling
- Cloud-based AI/data workloads
- Strong understanding of telecom operations/data
- Ability to bridge business and technical needs
- Excellent communication, stakeholder management, and leadership abilities