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Описание вакансии
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TL;DR
Senior Product Manager (Search Infrastructure): Owning search infrastructure for an AI-agent web access layer, including index coverage, freshness, retrieval quality, latency, and cost with an accent on high-scale search and ranking systems. Focus on setting quality and release bars, designing evaluation-driven tradeoffs, and shaping retrieval infrastructure for agentic workflows.
Location: Amsterdam, Netherlands. Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility.
Company
Nebius builds a full-stack AI cloud platform for data, model training, inference, and production deployment, with Tavily providing web access infrastructure for AI agents.
What you will do
- Set quality standards and release criteria for search products in partnership with the evaluation team.
- Own depth, latency, and cost tradeoffs across search products and make decisions explicit and defensible.
- Shape index coverage, freshness, and quality requirements, then turn the product direction into a roadmap.
- Develop a perspective on search infrastructure for AI agents and retrieval-based workflows.
- Compare product performance with alternatives and drive work to close important gaps.
- Work with customer success, customers, data teams, and vertical product owners to translate real-world feedback into quality priorities.
Requirements
- 5+ years of product management experience, including substantial work with high-scale search or ranking systems.
- Previous experience as an engineer, ML engineer, or researcher on a production web search, feed ranking, or advertising system is required.
- End-to-end experience shipping search or ranking changes and evaluating their impact.
- Strong ability to design experiments, interpret evaluation results, and distinguish meaningful quality improvements from noise.
- Strong understanding of LLMs, AI agents, retrieval, and agentic workflows.
- Ability to make product decisions, work through ambiguity, and influence cross-functional stakeholders without formal authority.
Nice to have
- Experience with information retrieval, NLP, or applied machine learning.
- Experience with index tiering, sharding, freshness pipelines, or cost-per-query optimization at scale.
- Experience with hybrid retrieval, semantic and lexical search, re-ranking, or human evaluation programs.
- Experience with API-first developer platforms, self-serve and enterprise products, or high-growth technology companies.
Culture & Benefits
- Competitive compensation and career growth opportunities.
- Learning opportunities, flexibility, and real ownership.
- Collaborative, innovative, and international environment.
- Opportunity to work on impactful AI projects with experienced engineering and research teams.
- Fast-moving environment focused on bold thinking, continuous growth, and meaningful impact.
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