Principal AI Architect & Governance

Vuori•Carlsbad, CA

About The Position

As Principal, AI Architect and Governance, you will serve as Vuori's senior technical authority for AI platform design, enterprise architecture standards, and responsible AI. You will define how AI systems are designed, built, integrated, and governed across the organization, ensuring they are secure, compliant, scalable, reliable, and aligned with business priorities. This senior role combines hands-on technical expertise with enterprise influence and has no direct people-management responsibility. You will work directly with engineers on architecture and design decisions, translate emerging AI capabilities into pragmatic enterprise patterns, and advise technology, business, security, legal, and data leaders on platform choices and risk. You will raise the quality and consistency of AI development through clear standards, reusable patterns, design reviews, and governance guardrails. The role includes shaping Vuori's enterprise AI architecture; establishing reference architectures, engineering standards, and integration patterns; evaluating AI platforms, foundation models, cloud services, and tooling; and making build-versus-buy-versus-partner recommendations. You will develop and operationalize the AI governance framework, including model risk management, data privacy, bias detection, audit trails, regulatory compliance, security guardrails, testing, evaluation, monitoring, incident response, and continuous improvement. You will partner with technology and business leaders, Legal, Compliance, Security, Data, and AI product, engineering, and data teams to align architecture and governance with organizational priorities and build requirements in from the start. You will mentor engineers and technical leads through architectural guidance and design reviews, track platform reliability, governance adherence, security posture, and business impact, and evolve standards and processes as the AI landscape changes.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
12+ years of experience in software engineering, platform engineering, or technology architecture, including significant experience owning enterprise AI or data platform architecture at scale.
Demonstrated experience designing and governing AI systems in production, including LLMs, agentic systems, ML pipelines, and model serving infrastructure.
Deep expertise in enterprise AI governance, risk management, security, and compliance frameworks.
Proven ability to define technical standards, make architecture decisions, and drive adoption across large, cross-functional engineering organizations through influence rather than direct authority.
Experience with cloud-native architectures on Azure, AWS, or Google Cloud, and modern AI infrastructure patterns including RAG, vector databases, and orchestration frameworks.
Experience building and deploying with frontier AI lab models, platforms, and/or frameworks, such as Anthropic, OpenAI, Google, or Meta.
Exceptional communication skills, including the ability to explain complex AI architecture and governance requirements clearly to engineering, business, and executive audiences.
Strong executive presence and demonstrated ability to build alignment, challenge assumptions constructively, and influence decisions across a matrixed organization.

Nice To Haves

Advanced degree in a related technical field.
Experience with enterprise AI governance platforms, model risk management frameworks, or AI regulatory standards such as the EU AI Act or NIST AI RMF.
Familiarity with MLOps, model lifecycle management, AI observability, and responsible AI tooling.
Experience with low-code and pro-code enterprise AI platforms such as Azure AI Foundry, Microsoft Copilot Studio, or Google Gemini Enterprise.
Background in retail, direct-to-consumer, e-commerce, or a similar consumer operating environment.
Demonstrated ability to establish and scale practical architecture standards and governance capabilities in high-growth organizations.
Active engagement with the broader AI and technology community through publications, speaking, or open-source contributions.

Responsibilities

Shape the evolution of Vuori's enterprise AI architecture to keep pace with business growth and the maturity of the AI ecosystem.
Establish reference architectures, engineering standards, and integration patterns for teams building AI systems.
Lead technical evaluations of AI platforms, foundation models, cloud services, and tooling, and recommend adoption decisions based on performance, cost, security, and business fit.
Improve architectural capability across engineering through design reviews, pairing, documentation, and reusable patterns.
Clarify complex problems, assess whether AI is the right solution, and communicate technical recommendations to technical and non-technical audiences.
Make build-versus-buy-versus-partner recommendations that shape the AI platform.
Develop and operationalize Vuori's AI governance framework, covering model risk management, data privacy, bias detection, audit trails, and regulatory compliance.
Establish AI engineering standards, security guardrails, testing and evaluation protocols, and responsible AI policies across teams.
Create governance structures that enable teams to build and ship AI responsibly while balancing innovation with enterprise risk management.
Partner with Legal, Compliance, Security, and Data teams to ensure AI systems meet applicable regulations, data handling requirements, and ethical standards.
Implement ongoing monitoring, incident response, and continuous improvement processes for AI systems in production.
Align AI architecture and governance with organizational priorities and investment decisions in collaboration with senior technology and business leaders.
Represent AI architecture and risk in discussions with executive sponsors, engineering leadership, external partners, and auditors.
Collaborate with AI product, engineering, and data teams to incorporate architecture and governance requirements from the start.
Mentor engineers and technical leads through architectural guidance, design reviews, and shared standards.
Track and report on platform reliability, governance adherence, security posture, and the business impact of AI architecture investments.
Assess emerging technologies, best practices, and industry standards and incorporate them into Vuori's AI ecosystem.
Use data and operational experience to refine standards, improve governance processes, and reduce friction for teams building AI responsibly.