AI Data Solutions Architect

Role

AI Data Solutions Architect

Location

New York City, NY / Newark, NJ / North Bergen, NJ – Onsite/Hybrid

Duration

12+ Months

Job Description

• Consultant to drive change across data and AI architecture – operationalizing an end‑to‑end data and AI approach, advancing taxonomy and ontology strategy, and standing up data onboarding standards with measurable SLAs.
• This role complements the existing team by adding temporary architecture expertise and hands‑on delivery.

Core Mandate

• End‑to‑end data & AI architecture: Define and operationalize a clear enterprise approach for how data and AI work together from ingestion through transformation, curation, serving, activation, and AI enablement.
• Taxonomy, ontology & semantic foundations: Drive clarity and progress on taxonomy, ontology, metadata, and semantic structure to support discoverability, analytics, personalization, governance, and AI use cases.
• Data onboarding standards & SLAs: Establish a consistent data onboarding model with measurable SLAs for speed, quality, ownership, lineage, documentation, and operational readiness.

What This Person Will Do

• Drive stakeholder alignment and decision‑making across architecture, governance, and operating model choices.
• Stand up reusable patterns and practical frameworks the team can apply immediately.
• Identify and unblock critical architectural and operational bottlenecks.
• Translate ambiguity into action, with visible progress during the engagement.
• Work side‑by‑side with the current team to embed changes that can be sustained after the engagement.

Ideal Profile

• Pragmatic and execution‑focused, able to maximize impact within existing platform choices rather than re‑opening foundational technology decisions.
• Brings practical ideas for improving team productivity, speed, and quality through better workflows, tooling, and AI‑assisted coding practices.

Expected Outcomes by End of Engagement

• A clear, adopted core data and AI architecture approach.
• An actionable taxonomy, ontology, and semantic strategy.
• A working data onboarding model with defined SLAs and quality gates across News Group data assets.
• Reusable standards, governance direction, and operating patterns in active use.
• A prioritized 6‑12 month roadmap and handoff materials for continuity.

Required Experience

• 10+ years in data architecture, data platform engineering, information architecture, or AI systems architecture.
• Deep enterprise data architecture expertise with strong hands‑on understanding of Databricks and medallion design.
• Strong experience in distributed data processing, data modeling, governance, observability, metadata strategy, and semantic modeling.
• Production experience with AI / LLM‑based systems, including RAG, vector databases, prompt orchestration, evaluation, monitoring, and governance controls.
• Understanding of fast‑evolving AI agent architectures.
• Deep understanding of how taxonomy, ontology, metadata, and semantic structures support scalable enterprise data and AI use cases.
• Deep working knowledge of Databricks and AWS, with the ability to architect and execute within already‑selected strategic platforms.
• Strong understanding of how to improve technical team productivity through modern AI‑assisted development tools such as GitHub Copilot, Claude Code, and Codex.