Senior Enterprise AI & Data Architect

Ralliant

About The Position

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.

Responsibilities

Enterprise AI & Data Strategy Execution
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
Business Model & Value Architecture
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
Platform Architecture & Implementations
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.
Data Management, Engineering Principles & Standards
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
Security, Privacy, and Compliance by Design
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.
Spend Optimization & FinOps
Work with Infrastructure, Cloud Engineering, and Finance to define FinOps-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
Governance, Operating Model & Ways of Working
Play a leading role in architecture governance forums to evaluate and approve AI/data solutions and platform investments.
Define decision-rights, standards, and patterns that enable dual-speed delivery
Partner with Innovation PODs, Citizen Development programs, and Operating Company teams to ensure architectures support both centralized and decentralized innovation safely
Stakeholder Leadership & Engagement
Serve as a trusted advisor to Operating Company Product, Commercial, Operations, and RBS leaders on how AI/data platforms and architectures unlock their strategic priorities.
Communicate complex architectural concepts in business language, linking design decisions to KPIs such as revenue growth, NDR, CSAT, margin, productivity, and time-to-market.
Champion Ralliant’s vision where every employee can build or orchestrate agentic workflows in their area, with architecture and platforms that make this safe and scalable.