Enterprise Data Architect

Position Title: Senior AI/ML Data Architect Location: Basking Ridge, NJ. Work Arrangement: Onsite This is a Principal/Enterprise Architect level role requiring a rare combination of Telecom + Data Architecture + GenAI/LLM/AI Architecture + Hands-on Engineering experience. Job Description: • We are seeking a Senior AI/ML Data Architect with strong expertise in Large Language Models (LLMs), AI agents, large-scale data systems, and end-to-end data pipeline creation, specifically within the Telecom domain. This role is responsible for architecting AI-ready data platforms that power intelligent automation, advanced analytics, and agent-based decision systems across OSS/BSS, network operations, and customer engagement. • The ideal candidate will bridge data architecture, AI/ML enablement, and telecom domain intelligence, enabling scalable, governed, and high-performance AI solutions. Key Responsibilities: 1. LLM & AI Agent Architecture • Design and implement LLM-enabled architectures, including RAG • (Retrieval-Augmented Generation) solutions using structured and unstructured telecom data. • Architect and govern AI agents and multi-agent systems for automation, diagnostics, decision support, and workflow orchestration. • Enable secure integration of LLMs and agents with enterprise data platforms, APIs, and business systems. • Define best practices for prompt engineering, model orchestration, evaluation, and feedback loops. 1. Large-Scale Data Architecture • Lead the design of large-scale, cloud-native data platforms capable of processing high-volume, high-velocity telecom data. • Architect low-latency and batch data ecosystems handling CDRs, network telemetry, logs, KPIs, customer interactions, and documents. • Select and implement appropriate data architecture patterns such as Lakehouse, • Streaming-first, and Data Mesh. 1. Data Pipelines & Engineering • Design and oversee end-to-end data pipelines covering ingestion, transformation, enrichment, feature creation, and serving layers. • Build AI-ready pipelines optimized for LLM training, inference, agent context retrieval, and model lifecycle management. • Ensure real-time and batch pipeline reliability using observability, data quality checks, and automated monitoring. • Implement CI/CD-driven pipeline deployments and versioning. 1. Telecom Domain Enablement • Partner with OSS, BSS, Network Engineering, IT, and Business teams to translate telecom use cases into scalable AI data solutions. • Apply deep understanding of telecom KPIs, network layers, subscriber data, and operational workflows. • Enable AI use cases including: • Network anomaly detection & root-cause analysis • Intelligent NOC and assurance automation • Customer experience analytics & churn prediction • Fraud detection and revenue assurance 1. Governance, Security & Compliance • Define and enforce data governance, lineage, metadata management, and accesscontrol for large data and AI systems. • Ensure compliance with data privacy regulations and secure AI usage across platforms. • Establish responsible AI and LLM governance frameworks. 1. Technical Leadership • Act as a domain expert and solution authority for AI/ML data architecture. • Define architectural standards, reference models, and reusable frameworks. • Mentor engineers, architects, and data teams. • Contribute to enterprise AI and data transformation roadmaps. Required Skills & Experience Experience • Overall 20+ years of IT experience • 12+ years in data engineering, data architecture, or analytics platforms • 5+ years working in the Telecom domain (Network, OSS/BSS, 4G/5G) • Proven experience delivering LLM-based and AI-driven data platforms Technical Skills • Strong expertise in LLMs, RAG architectures, and enterprise AI integration • Hands-on experience designing AI agents and agent orchestration frameworks • Hands on experience in developing, testing and deployment solution • Fully hands on coding experience in Python or Java • Deep knowledge of large-scale data systems (batch & streaming) • Expertise in creating robust, scalable data pipelines • Strong understanding of ML pipelines, feature engineering, and AI lifecycle needs • Advanced SQL and data modeling skills • Cloud experience with enterprise-scale AI and data workloads Domain & Soft Skills • Strong telecom data and operations knowledge • Ability to translate complex technical designs into business value • Excellent communication, stakeholder engagement, and leadership skills