Principal AI Architect & Governance

Vuori, Inc•Carlsbad, CA

1d•$197,500 - $264,390•Remote

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 individual-contributor role combines deep, hands-on technical expertise with enterprise influence and has no direct people-management responsibility. You will work 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 standards, reusable patterns, design reviews, and governance guardrails. You will shape Vuori’s enterprise AI architecture; establish reference architectures, engineering standards, and integration patterns; evaluate AI platforms, foundation models, cloud services, and tooling; and make build-versus-buy-versus-partner recommendations. You will develop and operationalize AI governance covering model risk management, data privacy, bias detection, audit trails, regulatory compliance, security, testing, and responsible AI. You will also partner across the organization to align AI architecture and governance with business priorities, guide teams in building requirements into systems from the outset, monitor production AI systems, and continually evolve standards and processes.

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 production AI systems, 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 such as 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 to engineering, business, and executive audiences.
Strong executive presence and demonstrated ability to build alignment, constructively challenge assumptions, 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 in line 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 tools, recommending adoption based on performance, cost, security, and fit.
Raise engineers’ architectural capability through design reviews, pairing, documentation, and reusable patterns.
Bring clarity to complex problems and identify when an AI approach is not the right solution.
Make and communicate build-versus-buy-versus-partner recommendations for the AI platform.
Develop and operationalize an AI governance framework addressing 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.
Create governance structures that enable responsible AI development while balancing innovation with enterprise risk management.
Partner with Legal, Compliance, Security, and Data teams to address regulations, data handling requirements, and ethical standards.
Implement ongoing monitoring, incident response, and continuous improvement processes for production AI systems.
Work with senior technology and business leaders to align AI architecture and governance with organizational priorities and investments.
Represent AI architecture and risk in conversations with executive sponsors, engineering leadership, external partners, and auditors.
Collaborate with AI product, engineering, and data teams so architectural and governance requirements are incorporated from the start.
Mentor engineers and technical leads through architectural guidance, design reviews, and shared standards.
Track and report platform reliability, governance adherence, security posture, and business impact of AI architecture investments.
Assess the AI landscape and incorporate emerging technologies, best practices, and industry standards.
Use data and operational experience to refine standards, improve governance processes, and reduce friction for teams building AI responsibly.