Job description

Who we are lululemon is an innovative performance apparel company for yoga, running, training, and other athletic pursuits. Setting the bar in technical fabrics and functional design, we create transformational products and experiences that support people in moving, growing, connecting, and being well. We owe our success to our innovative product, emphasis on stores, commitment to our people, and the incredible connections we make in every community we're in. As a company, we focus on creating positive change to build a healthier, thriving future. In particular, that includes creating an equitable , inclusive and growth-focused environment for our people. About this team The Enterprise Data & AI organization is a strategic and operational driver of growth for lululemon, owning and building the data and AI platforms and services that enable the enterprise to operate with intelligence at scale. The team leads the design and delivery of a trusted unified data foundation, AI-driven data analytics and insights, and AI solutions across lululemon’s vertically integrated retail ecosystem, while embedding strong data governance and responsible AI practices from the very beginning. By applying AI to critical business challenges and creating new, transformative AI solutions, the team helps reshape how lululemon operates. Through deep partnership with product, technology, and business teams, Enterprise Data & AI accelerates product innovation, unlocks measurable value, elevates guest and educator experiences, and drives enterprise efficiency.  Core responsibilities As a Principal AI/ML Engineer, you will define and drive implementation approaches for enterprise-scale AI initiatives that transform how lululemon operates and delivers value. You will leverage deep expertise in machine learning systems, generative AI, MLOps , and platform architecture to shape company-wide technical strategy and design of the enterprise AI platform and services, and AI solutions. You will collaborate closely with enterprise architects, applied science leaders, product leaders, and engineering organizations to translate the AI strategy and priorities into scalable technical solutions. Acting as a trusted advisor across the enterprise, you will guide critical decisions related to the architecture for enterprise AI platform and services, the evolution of the AI platform, and responsible AI implementation. You will operate as a hands-on technical leader, advisor, and thought leader, influencing organizational direction through your technical expertise, and as an individual contributor, guide the build of AI/ML engineering capabilities across the company.This role may require availability outside of standard business hours, including on-call support, based on business needs. Select responsibilities include: • Define the enterprise AI/ML engineering vision and implementation strategy spanning the enterprise AI platform and services, and common frameworks and tools for model development, training infrastructure, inference platforms, evaluation frameworks, and governance capabilities. • Drive implementation of major AI initiatives, ensuring scalable, reliable, secure, and cost-effective AI solutions across the enterprise. • Demonstrate expert-level coding proficiency by developing critical components of AI platforms, ML infrastructure, and production AI systems when hands-on technical leadership is required. • Partner with enterprise architects, product team, and the Data and AI team to shape company-wide AI architecture, providing deep technical expertise on implementation feasibility, operational considerations, scalability, and long-term maintainability. • Lead technical design of foundation model services, generative AI solutions, and agentic frameworks, • Challenge and improve existing AI architectures by identifying platform limitations, technical risks, and opportunities for innovation, proposing solutions that advance enterprise AI capabilities. • Provide executive-level technical advisory on complex AI investments, build-versus-buy decisions, model strategy, technology selection, responsible AI considerations, and implementation risk assessment. • Drive enterprise-wide AI/ML engineering practices including model lifecycle management, experimentation standards, evaluation methodologies, observability, reliability, and responsible AI controls. • Influence product strategy and business investment decisions through technical insights on AI feasibility, value realization, scalability, and organizational impact. • Drive engineering productivity and AI adoption across multiple teams through platform enhancements, reusable AI capabilities, automation, and reduction of systemic technical barriers. • Mentor Senior and Staff engineers while developing the next generation of AI technical leaders across the organization. • Represent lululemon externally through industry conferences, technical publications, open-source contributions, and participation in the broader AI community. Qualifications • Bachelor’s degree in computer science, Engineering, or related field, or equivalent experience; Master's preferred. • 11-15+ years of progressive software engineering and AI/ML engineering experience, including significant experience designing and operating enterprise-scale AI systems and platforms, or equivalent. • Expert-level coding ability with a track record of developing production-grade AI/ML systems, platforms, and infrastructure that solve highly complex technical and business challenges. Retail experience preferred. • Deep expertise across system design for complex ML solutions, model deployments, batch and real-time services, and evaluation frameworks. • Proven experience defining implementation strategies and execution approaches for complex, cross-organizational AI initiatives with measurable business impact. • Demonstrated ability to evaluate and guide adoption of emerging AI technologies • Deep experience analyzing complex technical trade-offs involving model quality, latency, reliability, scalability, cost optimization, privacy, and governance requirements. • Recognized expertise in implementing AI solutions combined with the ability to assess enterprise-wide implications and influence long-term technology direction. • Experience collaborating with applied science, product, architecture, security, and engineering leadership teams to deliver enterprise AI capabilities. • Advanced experience with implementing AI/ML engineering solutions using python , Spark, Airflow, MLFlow , feature stores, vector databases, model serving platforms, cloud AI services, Kubernetes, and modern MLOps tooling. Must haves • Acknowledge the presence of choice in every moment and take personal responsibility for your life. • Possess an entrepreneurial spirit and continuously innovate to achieve great results.  • Communicate with honesty and kindness and create the space for others to do the same.  • Lead with courage, knowing the possibility of greatness is bigger than the fear of failure.  • Foster connection by putting people first and building trusting relationships.  • Integrate fun and joy as a way of being and working, aka doesn’t take yourself too seriously.  additional notes Please note: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of employment visa at this time for this role. compensation and benefits package lululemon’s compensation offerings are grounded in a pay-for-performance philosophy that recognizes exceptional individual and team performance. The typical hiring range for this position is from $266,720 - $350,070   annually ; the base pay offered is based on market location and may vary depending on job-related knowledge, skills, experience, and internal equity. As part of our total rewards offering, permanent employees in this position may be eligible for our competitive annual bonus program and equity offerings, subject to program eligibility requirements.   At lululemon, investing in our people is a top priority. We believe that when life works, work works. We strive to be the place where inclusive leaders come to develop and enable all to be well. Recognizing our teams for their performance and dedication, other components of our total rewards offerings include support of career development, wellbeing, and personal growth: • Extended health and dental benefits, and mental health plans • Paid time off • Savings and retirement plan matching • Generous employee discount • Fitness & yoga classes • Parenthood top-up • Extensive catalog of development course offerings • People networks, mentorship programs, and leadership series (to name a few) Note: The incentive programs, benefits, and perks have certain eligibility requirements. The Company reserves the right to alter these incentive programs, benefits, and perks in whole or in part at any time without advance notice. workplace arrangement In-person collaboration and connection is important to our culture. Work is performed onsite, minimum 4 days per week. #LI-AG2

Requirements

Must-haves

Drive implementation of major AI initiatives, ensuring scalable, reliable, secure, and cost-effective AI solutions across the enterprise.
Demonstrate expert-level coding proficiency by developing critical components of AI platforms, ML infrastructure, and production AI systems when hands-on technical leadership is required.
Lead technical design of foundation model services, generative AI solutions, and agentic frameworks,
Challenge and improve existing AI architectures by identifying platform limitations, technical risks, and opportunities for innovation, proposing solutions that advance enterprise AI capabilities.
Provide executive-level technical advisory on complex AI investments, build-versus-buy decisions, model strategy, technology selection, responsible AI considerations, and implementation risk assessment.
Drive enterprise-wide AI/ML engineering practices including model lifecycle management, experimentation standards, evaluation methodologies, observability, reliability, and responsible AI controls.
Influence product strategy and business investment decisions through technical insights on AI feasibility, value realization, scalability, and organizational impact.
Drive engineering productivity and AI adoption across multiple teams through platform enhancements, reusable AI capabilities, automation, and reduction of systemic technical barriers.
Mentor Senior and Staff engineers while developing the next generation of AI technical leaders across the organization.
Represent lululemon externally through industry conferences, technical publications, open-source contributions, and participation in the broader AI community.
11-15+ years of progressive software engineering and AI/ML engineering experience, including significant experience designing and operating enterprise-scale AI systems and platforms, or equivalent.
Deep expertise across system design for complex ML solutions, model deployments, batch and real-time services, and evaluation frameworks.
Proven experience defining implementation strategies and execution approaches for complex, cross-organizational AI initiatives with measurable business impact.
Demonstrated ability to evaluate and guide adoption of emerging AI technologies
Deep experience analyzing complex technical trade-offs involving model quality, latency, reliability, scalability, cost optimization, privacy, and governance requirements.
Recognized expertise in implementing AI solutions combined with the ability to assess enterprise-wide implications and influence long-term technology direction.
Experience collaborating with applied science, product, architecture, security, and engineering leadership teams to deliver enterprise AI capabilities.
Acknowledge the presence of choice in every moment and take personal responsibility for your life.
Possess an entrepreneurial spirit and continuously innovate to achieve great results.
Communicate with honesty and kindness and create the space for others to do the same.
Lead with courage, knowing the possibility of greatness is bigger than the fear of failure.
Foster connection by putting people first and building trusting relationships.

Nice-to-haves

Bachelor’s degree in computer science, Engineering, or related field, or equivalent experience; Master's preferred.
Expert-level coding ability with a track record of developing production-grade AI/ML systems, platforms, and infrastructure that solve highly complex technical and business challenges. Retail experience preferred.

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aimlmachine learningpythonkubernetes

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