Role overview

Senior Engineering Manager, Search

Requirements and responsibilities

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About the job

  • Own the team's technical strategy, roadmap, and goals across Single and Cross retailer search, query understanding, suggestions, Ads on Search.
  • Drive top-line growth while holding a strict quality bar.
  • Champion the use of LLMs in search.
  • Partner with the platform team to design and ship the next-generation search retrieval architecture, while managing the latency and reliability tradeoffs of a tier-1 surface.
  • Double the team's experimentation velocity by investing in evaluation, AI-native debugging tooling, and ML foundations.
  • Partner closely with ML, Product, Data Science, the Home and Discovery Platform teams, the Ads organization, and whitelabel retailer teams to translate ranking changes into business and retailer outcomes.
  • Hire, develop, and coach engineers, and build an inclusive, high-trust team culture.

Minimum qualifications

  • 4+ years of engineering management experience leading high-performing teams, with minimum 10+ years of total engineering experience.
  • Direct experience building or leading search, recommendations, ranking, or other applied ML systems, as a manager or as a senior individual contributor.
  • Familiarity with modern retrieval techniques, including neural/semantic retrieval, ANN, and LLM-based query understanding or re-ranking.
  • Strong technical depth across machine learning and large-scale distributed/backend systems; able to set direction with and earn the trust of staff-level engineers.
  • A track record of driving complex, cross-functional technical programs from strategy through launch while holding a high bar for quality and reliability.
  • Demonstrated product and business judgment: able to connect modeling and ranking decisions to metrics like conversion and revenue, and to reason through tradeoffs (e.g., relevance vs. latency, organic vs. ads).
  • Strong communication and stakeholder skills; comfortable bridging technical and non-technical partners.

Preferred qualifications

  • Experience with ranking and personalization at scale: multi-stage rankers, multi-task deep models, embeddings, and real-time/session-based features.
  • Experience operating low-latency, high-throughput services with strict SLAs, including on-call and reliability ownership.
  • Experience leading a 0→1 or ambiguous product area, and driving alignment across teams where ownership boundaries are still forming.
  • Experience working with LLMs in production, and with experimentation/A-B testing infrastructure.
  • Exposure to two-sided marketplaces, e-commerce, or ads-adjacent ranking problems.
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