About the company
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale.
Responsibilities
- Design, implement, and operate large-scale indexing systems and data pipelines at the core of the search infrastructure.
- Develop and optimise indexing strategies balancing performance, freshness, and resource efficiency.
- Work on storage formats, compaction strategies, and update mechanisms to keep data accessible and current.
- Ensure reliability and predictability of pipelines under high-throughput conditions.
- Build well-tested components with clear responsibilities and interaction contracts, while remaining flexible as the system evolves.
- Define and implement observability primitives, including structured logs, metrics, and data quality signals across offline and nearline pipelines.
- Monitor throughput, resource usage, and cost, and drive optimisations when business needs require it.
- Collaborate with runtime and ML teams to ensure indexing outputs meet retrieval and ranking requirements.
- Enable safe experimentation on indexing strategies and data processing logic through controlled rollouts and clearly defined quality signals.
Requirements
- 8+ years of experience building production backend or data infrastructure systems.
- Strong Go experience; C++/Rust is a plus.
- Experience with large-scale data processing systems (10+ GiB/sec throughput, petabyte-scale datasets, etc.).
- Experience building or operating databases, storage systems, data planes, or indexing pipelines.
- Strong understanding of distributed systems, fault tolerance, consistency, and scalability.
- Experience running production systems and handling operational incidents.
- Systems-thinking mindset and ability to reason about end-to-end data flows.
- Helpful additional experience: distributed data processing frameworks such as Spark, Flink, MapReduce, or Beam; content systems including scraping, proxying, or anti-bot infrastructure; ad tech, social networks, or other large-scale content platforms; DBMS internals (open source or SaaS) and cloud infrastructure; open-source contributions or active involvement in the engineering community; competitive programming or CTF participation (ICPC, IOI, or similar); SHAD or similar advanced technical programmes; conference talks or technical publications.
- Coding interviews are part of the process.
- Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility as a condition of hire.
Conditions
- 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.
- Applicants may request accommodations during the application process.