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About This Role
Company Description
Vuori is re-defining what athletic apparel looks like: built to move and sweat in but designed with a casual aesthetic to transition into everyday life. We draw inspiration from an active coastal California lifestyle; an integration of fitness, creative expression and life. Our high energy fast paced retail environment is reflected in the clothes we make. We aim to inspire others to take on all aspects of their lives with clarity, enthusiasm and purpose…while having a lot of fun along the way. We are proud to be an outlet for opportunity and for personal growth and success.
Job Description
The Vuori AI team is laying the foundation for the future of Vuori's AI ecosystem, building the platforms, tools, and frameworks that power AI-driven productivity, workflow automation, intelligent decision-making, and agentic implementations across the business. Our mission is to transform how work gets done by leveraging modern AI technologies, autonomous agents, and intelligent systems to solve real business problems, accelerate innovation, and create measurable impact at scale.
As Sr. Director of AI Architecture & Governance, you will serve as Vuori's senior-most technical authority on AI platform design, enterprise standards, and responsible AI. You will set the architectural direction for how AI systems are built and integrated across the organization, and establish the governance frameworks that ensure those systems are secure, compliant, scalable, and trustworthy.
This role calls for a rare combination of deep technical expertise and organizational leadership — someone who can engage at the level of system design with engineers while also shaping AI strategy with executive and business partners. You will work across teams and functions to raise the quality and consistency of AI development at Vuori, and put in place the standards and guardrails that let teams innovate with confidence.
What you'll get to do:
Set direction and raise the bar
- Shape the evolution of Vuori's enterprise AI architecture, ensuring it keeps pace with the growth of the business and the maturity of the AI ecosystem.
- Establish reference architectures, engineering standards, and integration patterns that teams across Vuori use when building AI systems.
- Lead technical evaluations of AI platforms, foundation models, cloud services, and tooling — recommending adoption decisions based on rigorous analysis of performance, cost, security, and fit.
- Raise the architectural capability of engineers across Vuori through design reviews, pairing, documentation, and reusable patterns others adopt because they are good.
- Bring clarity to complex, ambiguous problems — including calling out when a proposed AI approach is not the right solution.
- Make build-versus-buy-versus-partner recommendations that shape the AI platform for years, and communicate the rationale clearly to technical and non-technical audiences.
Build and maintain AI governance
- 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 that apply consistently across all teams building AI systems.
- Create governance structures that give teams a clear path to building and shipping AI responsibly — balancing speed of innovation with enterprise-grade 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.
Partner across the organization
- Work closely with senior technology and business leaders to align AI architecture and governance with organizational priorities and investment decisions.
- Serve as a clear, credible voice on AI architecture and risk in conversations with executive sponsors, engineering leadership, and external partners or auditors.
- Collaborate with AI product, engineering, and data teams to ensure architectural and governance requirements are understood and built in from the start — not added after the fact.
- Mentor engineers and technical leads through architectural guidance, design reviews, and the development of shared standards they can apply independently.
Measure and evolve
- Track and report on platform reliability, governance adherence, security posture, and the business impact of AI architecture investments.
- Continuously assess the AI landscape and incorporate emerging technologies, best practices, and industry standards to keep Vuori's AI ecosystem well-positioned.
- Use data and operational experience to refine standards, improve governance processes, and remove friction for teams building AI responsibly.
Qualifications Who you are:
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field; advanced degree preferred.
- 15+ years of experience in software engineering or technology architecture, including 5+ years leading 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 develop and enforce technical standards and architectural principles across large, cross-functional engineering organizations.
- 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 (i.e. Anthropic, OpenAI, Google, Meta, etc.).
- Exceptional communication skills, with the ability to explain complex AI architecture and governance requirements clearly to engineering, business, and executive audiences.
- Strong leadership presence and experience building alignment across a matrixed organization without direct authority over all stakeholders.
- 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 build and scale architecture and governance programs in high-growth organizations.
- Active engagement with the broader AI and technology community through publications, speaking, or open-source contributions.
Additional Information Our investment in you:
At Vuori, we’re proud to offer the following to our employees:
- Health Insurance
- Savings and Retirement Plan
- Employee Assistance Program
- Generous Vuori Discount & Industry Perks
- Paid Time Off
- Wellness & Fitness benefits
The salary range for this role is $215,300 per year - $288,225 per year. This role is bonus eligible.
Vuori is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
All your information will be kept confidential according to EEO guidelines.
Salary Context
This $215K-$288K range is above the 75th percentile for AI Architect roles in our dataset (median: $179K across 32 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 9,653 AI roles we're tracking, AI Architect positions make up 1% of the market. At Vuori, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Architect roles pay a median of $230,000 based on 212 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,275. This role's midpoint ($251K) sits 9% above the category median. Disclosed range: $215K to $288K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Vuori AI Hiring
Vuori has 1 open AI role right now. They're hiring across AI Architect. Based in Carlsbad, CA, US. Compensation range: $288K - $288K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI Architect roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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