Senior Enterprise AI & Data Architect

Remote

The Enterprise AI & Data Architect is a senior, hands‑on architecture leader responsible for translating Ralliant’s Data & AI Strategy into executable architectures, platforms, and operating standards across all operating companies. This role sits at the intersection of business model design, platform engineering, and data governance; ensuring that agentic AI, data products, and digital business models can be deployed at scale while optimizing spend and reducing time‑to‑value.

You will define and govern the enterprise AI/data architecture that enables:

• Agentic AI workflows as a “system of action” on top of existing systems of record.
• An Enterprise Data & Knowledge Platform and domain‑focused AI platforms that connect data and knowledge across operating companies and use cases.
• New business models (e.g., analytics/insights‑as‑a‑service) and digital customer experiences aligned to OpCo strategic plans.

• Translate the enterprise Data & AI Strategy into an integrated AI/data architecture blueprint and multi‑year roadmap, aligned with strategic priorities, foundational readiness, and priority use cases
• Define architecture guardrails based upon guiding principles
• Partner with the AI/Data Strategy function and AI/Data Center of Excellence to ensure solution and domain architectures deliver expected KPIs

• Work with Operating Company leaders to design AI/data‑enabled business models (analytics‑as‑a‑service, digital service ecosystems, intelligent customer platforms, embedded AI in products) and translate them into concrete platform, data, and integration architectures.
• Use Business Model Canvas‑style frameworks to ensure that data, AI, and platform components are explicitly linked to revenue models, pricing, cost structure, and value delivery.
• Define patterns for data rights, data contracts, and productized data/AI services that support recurring revenue (ARR) and new business models

• Own the reference architecture for the Enterprise Data & Knowledge Platform and domain‑focused AI platforms
• Integrate with Operating Company data layers and systems of record
• Support agentic workflows that span end‑to‑end business processes
• Provide on‑platform analytics and automation for common processes
• Define environment and hosting patterns to support GCC High / FedRAMP, hybrid and air‑gapped deployments, and regulated workloads.

• Define and maintain enterprise data architecture standards across data modeling, data products, metadata, lineage, MDM/reference data, event streaming, and integration patterns.
• Partner with Data Engineering, BI/Reporting, and Platform Operations to codify reference implementations and golden patterns for Operating Company data layers and pipelines.
• Operationalize data lifecycle and data governance policies in the architecture
• Promote “zero‑barrier” data access (with appropriate controls) to improve data liquidity and reduce time to prepare data for AI

• Embed secure‑by‑design principles into all AI/data architectures, including identity and access management, data segmentation, tenant isolation, and role‑based access.
• Align architectures with CMMC, cybersecurity, and data protection requirements identified in OpCo strategic plans and enterprise risk frameworks.
• Collaborate with Security Architecture, GRC, and Legal/Privacy to ensure architectures support policy enforcement and defensible compliance.

• Work with Infrastructure, Cloud Engineering, and Finance to define Fin Ops‑aligned architectural standards
• Architect for “fewer, bigger, better” strategic platforms and partners to reduce duplicated capabilities and IT run costs while increasing reuse
• Provide TCO/ROI viewpoints and architecture options that reduce the cost to deliver AI solutions

• Play a leading role in architecture governance forums to evaluate and approve AI/data solutions and platform investments.
• Define decision‑rights, standards, and…