Enterprise Architect
Lucid MotorsNewark, CAPosted 23 February 2026
Tech Stack
Job Description
<div class="content-intro"><div><u><strong>Leading the future in luxury electric and mobility</strong></u></div>
<div>At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence. Vehicles that are intuitive, liberating, and designed for the future of mobility.</div>
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<div>We plan to lead in this new era of luxury electric by returning to the fundamentals of great design – where every decision we make is in service of the individual and environment. Because when you are no longer bound by convention, you are free to define your own experience.</div>
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<div>Come work alongside some of the most accomplished minds in the industry. Beyond providing competitive salaries, we’re providing a community for innovators who want to make an immediate and significant impact. If you are driven to create a better, more sustainable future, then this is the right place for you.</div></div><p>The <strong>Enterprise Architect</strong> is a strategic, hands-on leader who partners with the IT, Product, and Business leaders to unlock enterprise value through AI. Serving as Lucid’s trusted authority on AI architecture, this role shapes the end-to-end strategy—from opportunity discovery and platform selection to model governance and production-scale delivery. The Enterprise AI Architect drives cross-functional alignment, embeds AI best practices into product, IT, and business roadmaps, and cultivates an innovation-forward culture that elevates skills, transparency, and measurable impact across the organization. </p>
<p><strong>You Will:</strong></p>
<p><em>Strategic Architecture Governance</em></p>
<ul>
<li>Select, design, and implement AI capabilities across core Enterprise SaaS platforms—Salesforce (AgentForce), SAP S/4HANA BTP (Joule, AI Core), ServiceNow (Now Assist), and Microsoft 365 Copilot—building chatbots, autonomous agents, and embedded predictive/generative apps that elevate CRM, ERP, collaboration, and ITSM workflows.</li>
<li>Define the enterprise-wide AI reference architecture (LLMs, MLOps, vector DBs, RAG patterns, multimodal pipelines) that aligns Product, IT, and Business roadmaps.</li>
<li>Own AI technology standards, guardrails, and design patterns—balancing innovation velocity with security, privacy, and ethical use (NIST RMF, ISO 42001, EU AI Act readiness).</li>
<li>Define and maintain an enterprise-wide AI capability maturity model and staged adoption roadmap, setting clear gate criteria, ROI metrics, and compliance checkpoints so each domain (Product, IT, and Business) advances safely and predictably toward generative-AI at scale.</li>
</ul>
<p><em>Delivery Enablement</em></p>
<ul>
<li>Guide cross-functional teams in turning use-case backlogs into scalable AI services, proofs-of-concept, and production deployments.</li>
<li>Establish MLOps foundations—CI/CD for models, feature stores, observability, and Responsible-AI evaluation pipelines.</li>
<li>Partner with Security Legal on model provenance, IP protection, and third-party-model risk assessments.</li>
</ul>
<p><em>Value Realization Evangelism</em></p>
<ul>
<li>Publish quarterly AI impact scorecards that translate technical metrics (e.g., precision, latency, cost-per-inference) into business KPIs, and actively broadcast successes and lessons learned across exec forums and all-hands to sustain momentum and surface new opportunities.</li>
<li>Mentor domain architects and data scientists; run workshops that upskill engineers business stakeholders on the art-of-the-possible.</li>
</ul>
<p><strong>You Bring:</strong></p>
<ul>
<li>10+ years in enterprise architecture or large-scale software engineering, with <strong>5+ years designing and deploying AI/ML solutions</strong> (including generative AI/LLMs).</li>
<li>Demonstrated success operationalizing AI in at least two domains (e.g., manufacturing optimization, intelligent au ... (truncated, view full listing at source)
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