Senior Engineering Manager (AI Search & Retrieval)
- We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses.
- We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey.
- We're designing the future of autonomous marketing, taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do.
About the Team: AI Search & Retrieval
The AI Search & Retrieval team owns our core search platform, serving hundreds of millions of queries per day across enterprise customers. We build and operate highly scalable, low-latency systems that combine traditional information retrieval with modern ML-driven ranking, semantic understanding, and large-scale data processing—all in production at scale.
This team sits at the intersection of systems engineering, search relevance, and applied ML, with a direct impact on customer revenue and experience.
The Role
As a Senior Engineering Manager for AI Search & Retrieval, you will lead a high-performing team of engineers (including Senior Staff level talent) responsible for shaping the architecture and long-term evolution of our Search platform. You are a proven engineering leader who is passionate about mentoring technical talent, fostering a culture of psychological safety, and rallying a team to deliver on complex technical initiatives that directly contribute to business goals.
This role is ideal for someone who balances strong people leadership with deep technical empathy for Search domains, distributed systems, and modern AI/ML production systems.
What You’ll Do
Technical Leadership & Domain Strategy
- Evolve Search Architecture: Champion the technical roadmap and long-term strategy for core Search infrastructure, spanning indexing, retrieval, ranking, query-time execution, and data processing.
- Bridge Engineering & Applied Science: Partner closely with Applied Science and ML teams to productionize advanced ranking models, vector embeddings, and semantic retrieval techniques.
- System Excellence at Scale: Ensure search systems meet strict latency, availability, and cost-efficiency SLAs under heavy, real-world enterprise traffic.
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