Jobs at Faire

Build and own backend services, data pipelines, infrastructure, and experimentation systems that deliver machine-learning-generated product listing enhancements at catalog scale. The role involves productionizing data science outputs, monitoring quality and freshness, managing LLM and computer vision tradeoffs, launching experiments, and mentoring engineers while balancing product impact, reliability, cost, and maintainability.

Leads Faire’s Analytics Platform team, managing eight engineers and setting technical strategy for data warehousing, ETL/ELT pipelines, foundational datasets, BI tooling, governance, reliability, and cost efficiency. The role requires hands-on technical leadership, production issue management, AI-powered analytics tooling, cross-functional partnership, vendor management, and talent development. The manager will build scalable, trustworthy data systems used across engineering, data science, finance, product, and analytics.

Own the technical direction, development, reliability, and migration of Faire’s data infrastructure. Build CDC and streaming ingestion pipelines from production databases through Kafka into Iceberg on S3, operate Airflow and Fivetran, and implement data contracts, quality checks, SLAs, and observability. Lead cross-team initiatives, mentor engineers, manage incidents and on-call responsibilities, and partner with data scientists, analysts, and engineering teams to deliver dependable analytical data platforms.

Build and own advertiser-facing advertising features end to end, including campaign workflows, controls, reporting, and scalable product systems. Partner with Product, Design, Data Science, Analytics, Marketing, and Go-to-Market teams to identify opportunities and deliver solutions. Use AI tools in engineering workflows, instrument products, analyze experiments and advertiser behavior, and guide future investments through data.

Build and own production systems for Faire’s marketing organization, including landing pages, audience synchronization, campaign automation, paid media feeds, data layers, and recommendation tooling. Write production code, operate services end to end, participate in on-call, and integrate AI agents with evaluations, monitoring, and defined failure modes. Partner directly with marketing teams to turn ambiguous needs into scalable self-service capabilities.

Lead design and production of next-generation search and personalization systems using LLMs, dense vector retrieval, GNNs, multi-stage ranking, and reinforcement learning. Drive GPU-based deployment (e.g., Triton), ensure <100ms latency, mentor applied scientists and MLEs, and partner cross-functionally to productionize scalable, reliable search and recommendation experiences.

Lead the Compass agent product as the technical and science owner: design and ship agentic/LLM-powered features end-to-end, set evaluation and experiment frameworks, build data-driven models and tooling, and collaborate across backend, data, and frontend to raise agent quality and enable safe action-taking behaviors.

Lead design and build of high-scale, low-latency backend systems for premium ad formats. Define architecture for unified serving and rendering, enable experimentation and optimization, collaborate with Product/Design/Data Science, mentor engineers, and drive availability, scalability, and roadmap for ad formats.

Lead definition and execution of a company-wide experimentation and measurement platform. Build and scale centralized experimentation infrastructure (Eppo), integrate with the data ecosystem, establish governance, tooling, lifecycle management, measurement standards, and partner with Product, Data Science, Analytics, and Strategy to drive rigorous experiment-driven decision-making.