OVERVIEW Live the experience. From professional empowerment to continual learning opportunities. From ongoing investment in new and emerging technologies to a career of self-determination. At Ulta Beauty, our tech team is critical to our scalability—and is recognized that way. We’ve been defined as a “mature start-up.” A place where interdepartmental exposure, open doors, and genuine collaboration is ubiquitous. Where challenges come fast and furious, requiring agility, mental dexterity, and creativity. Where our passion for better solutions drives us and is core to who we are. We’re engineering for the future of retail, and it’s no-holds-barred. But for those motivated by continual change and ambiguity, by superior leadership, by whip smart colleagues who will press you daily for your very best, you’ll find that virtually nothing’s impossible at Ulta Beauty. COMPANY: Ulta Beauty Credit Services Corporation LOCATION: 1000 Remington Blvd., Suite 120, Bolingbrook, IL 60440 TITLE: Sr Artificial Intelligence/Machine Learning (AIML) Engineer HOURS: Monday to Friday, 8:00 am to 5:00 pm DUTIES: Lead the full lifecycle execution of complex AI initiatives, bridging the gap between exploratory data science and production engineering, including formulation and statistical modeling to deployment and scaling. 20.0% Develop and optimize advanced algorithms for recommendation and decision engines, utilizing techniques such as collaborative filtering, embeddings, clustering, reinforcement learning, and constrained optimization. 15.0% Design pipelines for Large Language Models (LLMs) including fine-tuning, RAG (Retrieval-Augmented Generation), and prompt engineering for enterprise retail use cases like analytics augmentation and decision support. 15.0% Take ownership of the non-functional requirements of AI systems, explicitly optimizing models for low-latency inference, high throughput, data privacy compliance, and cloud cost efficiency. 10.0% Transition code from experimental notebooks to modular, version-controlled software packages. Implement automated training pipelines, CI/CD for ML, and robust monitoring for data drift and model degradation. 10.0% Contribute to and enforce engineering standards within the Enterprise AI team, including unit testing, documentation, peer code reviews, and reproducibility frameworks. 5.0% Partner with business and IT product teams to refine vague use cases into concrete engineering requirements, identifying technical risks early in the project planning process. 5.0% Map out detailed technical roadmaps, providing accurate time and effort estimates for both the research (Data Science) and implementation (Engineering) phases of projects. 5.0% Mentor junior team members and peers on both statistical best practices and software engineering principles, fostering a team culture of technical excellence. 10.0% Present technical results and architectural decisions to senior stakeholders, effectively communicating the trade-offs between model complexity, performance, and cost. 5.0% REQUIREMENTS: Master’s degree in Computer Science, Mathematics, Physics, Statistics or other quantitative field. Three (3) years in any occupation with experience working in data science, machine learning or AI.Three (3) years in any occupation with experience working in data science, machine learning or AI must include: Three (3) years of experience working in the Retail Industry. Three (3) years of experience writing production-quality object-oriented code such as Python or C++ and working with ML frameworks such as scikit-learn, TensorFlow, or similar, including three (3) years of experience building low-latency or real-time ML systems. Three (3) years of experience designing, building, and deploying large-scale recommender or decisioning systems, including techniques such as ranking, clustering, and other unsupervised learning methods. Three (3) years of experience applying optimization techniques in production environments, including large-scale ML or decisioning systems such as operational research, offer optimization, or revenue maximization. Three (3) years of experience building and deploying production ML systems on cloud platforms such as Google Cloud, Azure or AWS. Three (3) years of experience building scalable, production-grade real-time inference services using Docker, with CI/CD and monitoring. Two (2) years experience building or integrating large-scale batch ML pipelines using cloud-native event-driven systems such as Pub/Sub and containerized execution such as GKE. One (1) year of experience designing and developing reinforcement learning models in real-world or production settings. One (1) year of experience working with large language models (LLMs). Experience must also include: Experience working with large-scale data processing and analytics platforms, including Apache Spark and Databricks, for feature engineering, model training, and data pipelines; Experience with relational databases including Postgres, Bigquery and MySQL; Document databases including MongoDB; and lowlatency databases including BigTable; and Experience building and delivering complex ML solutions from inception to launch. TELECOMMUTING EMPLOYEE: Reports to company headquarters in Bolingbrook, IL. Can work remotely or telecommute up to 100%. SALARY: $165,984 - $166,984 per year The pay range for this position is $165,984.00 - $166,984.00 / Year with the opportunity for eligible associates to earn additional compensation pursuant to the Company’s bonus plan. Exact pay will be based on factors including, but not limited to relevant education, qualifications, certifications, experience, level, shift, geographic location, and business and organizational needs. Full-time positions are eligible for paid time off, health, dental, vision, life and disability benefits. Part-time positions are eligible for dental, vision, life, and disability benefits. For additional information concerning our benefits, visit our Benefits and Career Development page: https://learn.bswift.com/ulta ABOUT At Ulta Beauty (NASDAQ: ULTA), the possibilities are beautiful. Ulta Beauty is the largest North American beauty retailer and the premier beauty destination for cosmetics, fragrance, skin care products, hair care products and salon services. We bring possibilities to life through the power of beauty each and every day in our stores and online with more than 25,000 products from approximately 500 well-established and emerging beauty brands across all categories and price points, including Ulta Beauty’s own private label. Ulta Beauty also offers a full-service salon in every store featuring—hair, skin, brow, and make-up services. We will consider for employment all qualified applicants, including those with arrest records, conviction records, or other criminal histories, in a manner consistent with the requirements of any applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York City Fair Chance Act.

• Build AI-Powered Developer Tools: Design, implement, and ship production-ready AI agents and tools that accelerate developer productivity such as code review and refactoring assistants, automated test generators, local environment setup tools, deployment pipeline diagnostic agents, and on-call assistance tools • Implement LLM Integrations: Build robust, production-grade integrations with LLM APIs (OpenAI, Anthropic, etc.) such as prompt engineering, response parsing, error handling, rate limiting, cost management, and performance optimization • Develop Agent Orchestration Systems: Create agent frameworks and orchestration systems that enable complex multi-step workflows, tool calling, context management, and agent-to-agent communication • Contribute to Platform Infrastructure: Build self-service platform capabilities that enable teams across to rapidly deploy and operate their own AI developer tools such as deployment pipelines, observability integration, security controls, and operational tooling • Drive Adoption of AI-Native Development: Build tools and programs that accelerate adoption of AI developer tools such as Claude Code, Cursor, and Warp across engineering organization • Ensure Production Quality: Write well-tested code with strong test coverage (unit, integration, end-to-end); establish monitoring, alerting, and operational excellence for AI systems • Collaborate Cross-Functionally: Partner with Principal Engineer on architecture, work with product and design teams on features and UX, and collaborate with platform teams (Infrastructure, Security, Data) on integrations • Participate in Operations: Take part in on-call rotation for AI developer tools; respond to incidents, debug production issues, and drive continuous improvement of system reliability • Mentor and Share Knowledge: Guide other engineers through code reviews, pair programming, and technical discussions; document patterns and best practices for AI tool development • Measure and Iterate: Instrument AI tools to measure adoption, effectiveness, and developer productivity impact; iterate based on data and user feedback to continuously improve developer experience • On-Call Rotation: Take part in on-call rotation for your team; respond to incidents, debug production issues, and drive continuous improvement of system reliability

• Core Platform Development: Responsible for the development of the core agent platform components. • Architecture Transition: Lead the transition from a JavaScript prototype to a segregated Python application with dedicated Management APIs and Agent Execution Backends. • Agent Orchestration: Build and manage complex agent workflows using LangChain and LangGraph to handle multi-step interactions and tool calls. • No-Code & Pro-Code Tooling: Develop a platform that allows administrators to build agents via a "no-code" approach while enabling advanced users to execute custom code scripts. • RAG & Search Optimization: Implement advanced retrieval strategies, including hybrid search and rerankers, while justifying database choices through proof-of-concept metrics. • Guardrails & Compliance: Ensure AI safety by implementing logits masking, context managers, and content guardrails to prevent harmful or off-brand generation.

ABOUT THE ROLE Reporting directly into the CIO organization, you will be the lead architect and "ace technologist" responsible for the next era of Peloton’s internal evolution: Agentic AI. You will go beyond simple chatbots to build autonomous and semi-autonomous AI agents that execute complex workflows across Finance, Supply Chain, Marketing, Legal, and the People Team. This role is for a hands-on coder who can also set the strategic technical roadmap for enterprise-wide automation. YOUR DAILY IMPACT AT PELOTON - Architect and code multi-agent systems that can reason, use tools, and execute end-to-end business processes (e.g., automated financial reconciliation, legal contract analysis, or supply chain demand forecasting) - Partner with leaders in Finance, Marketing, Legal, and HR to translate their complex operational challenges into concrete AI architectures - Evaluate the latest agentic frameworks and LLM providers to decide when to leverage third-party tools and when to build proprietary enterprise solutions - Design highly available inference services and manage model serving at scale, ensuring these agents integrate seamlessly with existing corporate service meshes - Implement "Security by Design," creating automated guardrails for PII/PHI filtering and mitigating prompt injection to ensure enterprise data remains secure - Optimize the "Total Cost of Ownership" by managing trade-offs between agent reasoning depth (latency) and compute costs through intelligent caching and specialized routing YOU BRING TO PELOTON - 8–10+ years in software engineering, with at least 2 years of deep focus on AI/ML infrastructure or data engineering at scale - Mastery of Python, Go, or Java/Scala, with a strong grasp of distributed systems and microservices - Proven experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex) and deep understanding of vector databases (e.g., Pinecone, Milvus, Weaviate) - Hands-on experience with modern data stacks (Spark, Kafka, Snowflake, Databricks) and cloud environments (AWS, GCP, or Azure) - Expert knowledge of Kubernetes, Docker, and CI/CD patterns specifically for machine learning lifecycles #LI-DD1 #LI-Remote The base salary range represents the low and high end of the anticipated salary range for this position to be performed remotely from any Peloton office or facility, in any U.S. State and any location therein. The actual base salary offered for this position will depend on numerous factors including, without limitation, experience and business objectives. Our base salary is just one component of Peloton’s competitive total rewards strategy that also includes annual equity awards and an Employee Stock Purchase Plan as well as other region-specific health and welfare benefits. As an organization, one of our top priorities is to maintain the health and wellbeing for our employees and their family. To achieve this goal, we offer robust and comprehensive benefits including: - Medical, dental and vision insurance - Generous paid time off policy - Short-term and long-term disability - Access to mental health services - 401k, tuition reimbursement and student loan paydown plans - Employee Stock Purchase Plan - Fertility and adoption support and up to 18 weeks of paid parental leave - Child care and family care discounts - Free access to Peloton Digital App and apparel and product discounts - Commuter benefits and Citi Bike Discount - Pet insurance and so much more! Base Salary Range $172,250—$240,350 USD ABOUT PELOTON: Peloton (NASDAQ: PTON) provides Members with expert instruction, and world class content to create impactful and entertaining workout experiences for anyone, anywhere and at any stage in their fitness journey. At home, outdoors, traveling, or at the gym, Peloton brings together innovative hardware, distinctive software, and exclusive content. Founded in 2012 and headquartered in New York City, Peloton has millions of Members across the US, UK, Canada, Germany, Australia, and Austria. For more information, visit www.onepeloton.com. Peloton is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. Equal employment opportunity has been, and will continue to be, a fundamental principle at Peloton, where all team members, applicants, and other covered persons are considered on the basis of their personal capabilities and qualifications without discrimination because of race, color, religion, sex, age, national origin, disability, pregnancy, genetic information, military or veteran status, sexual orientation, gender identity or expression, marital and civil partnership/union status, alienage or citizenship status, creed, genetic predisposition or carrier status, unemployment status, familial status, domestic violence, sexual violence or stalking victim status, caregiver status, or any other protected characteristic as established by applicable law. This policy of equal employment opportunity applies to all practices and procedures relating to recruitment and hiring, compensation, benefits, termination, and all other terms and conditions of employment. If you would like to request any accommodations from application through to interview, please email: applicantaccommodations@onepeloton.com. At Peloton, we embrace technology, including AI, to enhance productivity and accelerate innovation in the work we do for our members. However, in our hiring process, our priority remains in getting to know you and your unique qualifications. To ensure a fair and equitable process, we do not permit the use of AI tools during any stage of the application and interview process. In considering you as an applicant, we want to understand your skills, experiences, and motivations without mediation through an AI system. We also want to directly assess your communication skills without the use of an AI tool. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance and the San Francisco Fair Chance Ordinance, as applicable to applicants applying for positions in these jurisdictions. Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Peloton does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted here on our careers page and all communications from the Peloton recruiting team and/or hiring managers will be from an @onepeloton.com email address. If you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Peloton, please email applicantaccommodations@onepeloton.com before taking any further action in relation to the correspondence. Peloton does not accept unsolicited agency resumes. Agencies should not forward resumes to our jobs alias, Peloton employees or any other organization location. Peloton is not responsible for any agency fees related to unsolicited resumes.