AI/ML Data Architect

Role - Senior AI/ML Data architect

Location – Basking Ridge ,NJ- Hybrid

Work Mode – Hybrid (Client)

Need 20+ years of overall experience along with Telecom Background.

we need combination of folks who have experience and expertise on both Data Architecture along with AI/ML .

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:

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.

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.

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.

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

Governance, Security & Compliance

Define and enforce data governance, lineage, metadata management, and access control 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.

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:

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

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.