Senior Product Manager, Search Infrastructure
About this role
Managing the depth, latency, and cost tradeoffs of a web access layer for AI agents forms the core of daily responsibilities in this position. The team builds and operates its own index serving millions of developers and Fortune 500 companies, addressing large-scale crawl coverage, freshness, and query economics. This hands-on senior individual contributor role defines quality bars, shapes future index coverage, and establishes a roadmap for infrastructure designed specifically for autonomous agent consumption rather than human users.
Operating within a small product team at Nebius, the person in this seat collaborates directly with search engineering, research, evaluation, and customer success groups. Ideal candidates bring a technical background as an engineer, machine learning engineer, or researcher alongside extensive product management experience in high-scale search, ranking, or ad engines. The role suits a data-driven strategist who thrives in ambiguous environments and can defend complex technical tradeoffs to experienced engineers.
What you will do
- Establish the quality bar and release criteria for search products by defining acceptable standards for each use case.
- Manage depth, latency, and cost tradeoffs across search infrastructure to ensure explicit and defensible operational decisions.
- Shape the strategic direction of the index regarding coverage, freshness, and quality requirements.
- Develop a product roadmap anticipating how search infrastructure must adapt as autonomous agents become primary consumers.
- Analyze competitive alternatives and drive initiatives that close critical capability gaps.
- Partner with customer success and interact directly with users to translate workflow shortcomings into actionable quality priorities.
- Collaborate with data and vertical product owners to determine corpus requirements and industry-specific result shaping.
What you need
- Bring five or more years of product management experience with a significant focus on high-scale search, ranking systems, or ad engines.
- Possess a professional background as an engineer, machine learning engineer, or researcher on production systems within relevant domains.
- Demonstrate direct experience shipping search or ranking changes end to end, including evaluation and post-shipment analysis.
- Maintain a strong data foundation capable of experiment design, critical evaluation of results, and separation of quality improvements from statistical noise.
- Exhibit product judgment sufficient to determine development priorities and defend decisions to both engineering teams and customers.
- Understand large language models, AI agents, and the integration of retrieval within agentic workflows.
- Demonstrate comfort with ambiguity and the ability to navigate fluidly between strategy and execution.
Nice to have
- Depth in information retrieval, NLP, or applied machine learning beyond core requirements
- 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 in API-first or developer-platform businesses running both self-serve and enterprise motions
- Experience in a high-growth technology company, startup-within-a-larger-org, or post-acquisition environments
Benefits
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
Skills and tech stack
Questions candidates ask
Where is the role located?
The position is based in London, United Kingdom. Nebius is headquartered in Amsterdam with a global footprint and R&D hubs across Europe, the UK, North America, and Israel.
Who will I report to and work with?
This is a hands-on senior IC role reporting to the Director of Product. You will work day to day with search engineering and research teams, the evaluation team, and customer success.
What is the expected background for applicants?
Applicants must have five plus years of product management experience with a meaningful portion spent on high-scale search or ranking systems. A background as an engineer, ML engineer, or researcher on a production system in one of those areas is required.
What are the core duties regarding search infrastructure?
You will own depth, latency, and cost tradeoffs across search products and make them explicit and defensible. You also set the quality bar and release criteria for search and shape the direction of the index.