Looking for AI Architect in - NYC Hybrid - W2 only

Role name: AI Architect
Work site: NYC Hybrid
Start date: Immediate availability.
Background check MANDATORY
Job Description: Role Summary
Interim Consultant, Data, Taxonomy & AI Architecture Transformation
6-month external 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
1. 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.
2. 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.
3. 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