Senior Product Manager Personalization Ai

## About the Role We're looking for a Senior Product Manager, Personalization & AI to lead the product vision, strategy, and execution of two interconnected pillars: our next-gen personalization systems (menu ranking, recommendations, search, predictive preferences, and adaptive UI) and a new customer-facing AI experience powered by LLMs. This role will own both the personalization engine across the entire eater journey and the 0→1 build of a customer-facing AI experience—and will work cross-functionally with ML, LLM engineering, frontend and backend engineering, data science, design, and our culinary teams to build a highly adaptive, intelligent food experience. You'll go deep into understanding eater behaviors, intent signals, and food preferences, and translate them into a scalable roadmap across both personalization and conversational AI that meaningfully lifts retention, conversion, and LTV. Our users make hundreds of micro-decisions every week; the goal is to simplify all of them—whether through intelligent ranking or a natural-language experience. ## What You'll Do ### Define & Drive Product Strategy - Own the end-to-end personalization roadmap including recommendations, ranking algorithms, adaptive feed, intent modeling, and predictive food preferences. - Build a unified personalization strategy that spans discovery, ordering, search, and post-order experiences. - Translate customer insights and behavioral data into frameworks for "personalized ordering journeys" across weekly menus. ### Ship High-Impact Personalization Features - Partner with Engineering and ML to design, build, and iterate on models that personalize menus, recommendations, and content surfaces. - Launch new ML-powered features—e.g., personalized ranking, contextual suggestion surfaces, food-intent clustering, dietary preference modeling, and personalization-aware UX. - Drive experimentation, A/B testing, and offline/online model evaluation frameworks to measure lift rigorously. ### Build the Customer-Facing AI Experience (0→1) - Own the 0→1 product vision and roadmap for a customer-facing conversational AI experience—from problem definition and early MVP through launch and iteration. - Define use cases, conversation flows, and success criteria, balancing eater needs with technical feasibility and business goals. - Partner closely with LLM engineering to evaluate models, define grounding strategies, and drive prompt/context architecture decisions from a product lens. - Own the full frontend product surface for the AI experience end-to-end, from UX vision through shipped features. - Establish evaluation frameworks for LLM product quality—including relevance, hallucination rate, tone, and task completion—and iterate based on real user feedback. ### Deeply Understand Customer Behavior - Develop a sophisticated understanding of eater behavior patterns, including early-week ordering signals, cuisine preferences, dietary constraints, and long-term engagement drivers. - Work closely with Data Science to identify behavioral segments, affinity clusters, and downstream retention impacts. ### Cross-Functional Leadership - Own the end-to-end frontend product surface for the customer-facing AI experience, partnering closely with Design and Engineering from concept through launch. - Collaborate on personalization-related frontend surfaces (adaptive homepage, personalized filters, recommendation UI)—contributing product direction while partnering with other PMs and Design who share ownership. - Work with Chefs and Culinary to incorporate menu diversity, cuisine metadata, and ingredient-level signals into both personalized and AI-assisted experiences. - Collaborate with Growth, CRM, and Marketplace teams to personalize acquisition, onboarding, and reactivation journeys. ### Drive Measurable Business Impact - Improve core funnel metrics (CVR, add-to-cart rate, search success rate). - Lift order retention, order frequency, and net AOV for all eater segments. - Increase long-term revenue and reduce decision friction for customers navigating a large menu. ## You Are - Experienced in ML-powered product development, ranking algorithms, recommendations systems, or personalization platforms. - Excited about building 0→1 conversational AI products and comfortable navigating the ambiguity of LLM-powered experiences. - Technically grounded in how LLMs work—prompting, RAG, evaluation, guardrails—and able to partner fluently with LLM engineers. - Analytical, systems-oriented, and comfortable with experimentation frameworks, model evaluation, and user behavior analytics. - A strong frontend product thinker who can own customer-facing UX and translate backend AI capabilities into intuitive, delightful user experiences. - Skilled at simplifying complex technical problems into user-centric solutions. - Excited by the challenge of turning a large, dynamic food catalog into a highly personalized weekly experience. - Collaborative, decisive, and able to partner tightly with Engineering, ML, Design, and cross-functional product groups. - Customer-obsessed and eager to understand why users choose the meals they do—and how to anticipate their next choice. ## Qualifications - 7+ years of product management experience, including at least 4+ years working on personalization, search, recommendations, ML/AI products, or similar domains. - Experience with LLM-powered products, conversational AI, or chatbot development—hands-on 0→1 experience a strong plus. - Strong analytical and technical intuition; can work closely with ML/infra teams and reason about relevance, ranking, and experimentation approaches. - Proven ability to drive complex products from concept to launch in fast-paced environments. - Experience with A/B testing platforms, online metrics, offline model evaluation, and data-driven decision making. - Demonstrated ability to own customer-facing frontend product surfaces end-to-end, from UX vision through launch. - Strong user experience instincts with a track record of collaborating closely with design. - Excellent communication skills and ability to articulate complex ideas to technical and non-technical stakeholders.