Staff / Senior Software Engineer (Agentic Search) - Index
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Job description
We are looking for a Senior Software Engineer to work on the indexing and data processing layer of a novel search engine tailored for agentic AI consumption. In this role, you will focus on building systems that ingest, process, and organize massive volumes of data into efficient, queryable structures. You will work primarily on offline and near-line pipelines, ensuring that data is fresh, complete, and efficiently accessible by downstream retrieval systems. You will operate in an environment where throughput, scalability, and correctness are critical; designing systems capable of handling tens of gigabytes per second across continuously evolving datasets.
In This Position, Your Responsibility Will Be To
- Design, implement, and operate large-scale indexing systems and data pipelines that sit at the core of our 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 near-line 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
- 5+ 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
Strong Candidates May Also Have Experience With
- 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
Benefits & 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
What’s It Like To Work At Nebius
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
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, 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.
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