Job description

About Faire Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. About the Role: The Discovery Search team (Search FX) sits at the intersection of search, evaluation, and personalization shaping how retailers find the products they love. Our mission is to build the most intuitive, intelligent, and delightful discovery experience in wholesale: one that feels less like a search engine and more like a trusted merchant with an encyclopedic knowledge of what's in stock and what will sell. As a Staff Engineer on the Search FX team, you will be a primary technical architect for our retailer-facing search surfaces. You will own the technical roadmap for search, recommendations, and Gen-AI experiences that drive a meaningful share of marketplace engagement. You will bridge the gap between high-scale infrastructure and world-class UX, helping unify retrieval, ranking, and personalization into a cohesive, high-performance system. You’re excited about this role because... You will own the technical vision: Define the end-to-end architecture for Faire's search and discovery experience, ensuring it is fast, relevant, and deeply personalized. You’ll build at the AI frontier: Integrate LLM-powered capabilities, such as natural language search and intelligent query understanding, directly into the product. You’ll solve complex scale problems: Help build high-scale, low-latency systems that navigate millions of products while meeting strict industry latency benchmarks. You’ll drive cross-functional impact: Partner closely with Data Science, Product, and Design to iterate on ranking models and UX components. You’ll be a mentor and leader: Foster a culture of engineering excellence and ownership, upskilling the team on technical expertise and decision-making. What You'll Do: Architect Next-Gen Search: Lead the design of composable grids, intent-aware routing, and orchestration layers that unify retrieval and ranking. Modernize Query Understanding: Leverage LLMs to consolidate the QU stack, improving accuracy for long-tail queries and edge cases. Optimize Performance: Drive initiatives to increase retrieval candidates (e.g., 10x growth) while maintaining stable search latency. Launch AI-Driven Features: Develop systems like "Search Missions" that use offline pipelines and LLMs to recover failed search sessions through expanded queries. Bridge AI and UX: Work with client engineers on SDUI and React Server Components to improve performance and developer velocity for dynamic search layouts. System Ownership: Take accountability for the reliability and observability of the search funnel, from query planner refactors to real-time retrieval monitoring. Qualifications: Experience: 7+ years of professional software engineering experience, with 3+ years as a technical leader driving complex, cross-team projects. Product Sensibility: A strong user-first mindset and the ability to translate ambiguous business problems into clear technical direction. AI/ML Familiarity: Experience partnering with Data Science to deploy and leverage machine learning and gen-AI systems in search experiences across ranking and retrieval. Domain Expertise: knowledge of search/query processing, including traditional, semantic, and hybrid frameworks (e.g., Elasticsearch, Lucene). Technical Stack: Strong programming skills in Kotlin or Java, with experience in high-performance backend systems, Protocol Buffers, and MySQL. Strategic Leadership: Demonstrated ability to contribute to team strategy without supervision and influence the broader organizational roadmap. Technologies We Use and Teach: Backend: Kotlin, Java 16, Hibernate, Guice, Jersey Search/Data: Elasticsearch, FAISS, Redis, DynamoDB Communication: Protocol Buffers, HTTP, JSON Infrastructure: AWS, Kubernetes, Buildkite, Datadog Salary Range: San Francisco & New York: the pay range for this role is $231,000 - $318,000 per year. This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future. Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting. Why you’ll love working at Faire Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly. Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day. Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours. Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work. Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success. Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog . Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression. Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form ( bit.ly) Privacy For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (faire.com)

Requirements

Must-haves

Architect Next-Gen Search: Lead the design of composable grids, intent-aware routing, and orchestration layers that unify retrieval and ranking.
Modernize Query Understanding: Leverage LLMs to consolidate the QU stack, improving accuracy for long-tail queries and edge cases.
Optimize Performance: Drive initiatives to increase retrieval candidates (e.g., 10x growth) while maintaining stable search latency.
Launch AI-Driven Features: Develop systems like "Search Missions" that use offline pipelines and LLMs to recover failed search sessions through expanded queries.
Bridge AI and UX: Work with client engineers on SDUI and React Server Components to improve performance and developer velocity for dynamic search layouts.
System Ownership: Take accountability for the reliability and observability of the search funnel, from query planner refactors to real-time retrieval monitoring.
Experience: 7+ years of professional software engineering experience, with 3+ years as a technical leader driving complex, cross-team projects.
Product Sensibility: A strong user-first mindset and the ability to translate ambiguous business problems into clear technical direction.
AI/ML Familiarity: Experience partnering with Data Science to deploy and leverage machine learning and gen-AI systems in search experiences across ranking and retrieval.
Domain Expertise: knowledge of search/query processing, including traditional, semantic, and hybrid frameworks (e.g., Elasticsearch, Lucene).
Technical Stack: Strong programming skills in Kotlin or Java, with experience in high-performance backend systems, Protocol Buffers, and MySQL.
Strategic Leadership: Demonstrated ability to contribute to team strategy without supervision and influence the broader organizational roadmap.
Backend: Kotlin, Java 16, Hibernate, Guice, Jersey
Search/Data: Elasticsearch, FAISS, Redis, DynamoDB
Communication: Protocol Buffers, HTTP, JSON
Infrastructure: AWS, Kubernetes, Buildkite, Datadog
Why you’ll love working at Faire
Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.
Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.
Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.
Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.
Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.

Nice-to-haves

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Keywords to mirror

machine learningaillmreactmlkotlinjavaawskubernetesgoaccessibility

Platform: greenhouse
Effort: quick

Benefits

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