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About Nebius: 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 seeking a Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact Benefits & Perks: 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 Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

About Nebius: 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 seeking a Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact Benefits & Perks: 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 Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

About Nebius: 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 seeking a Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact Benefits & Perks: 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 Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

About Nebius: 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 seeking a Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact Benefits & Perks: 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 Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

About Nebius: 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 seeking a Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact Benefits & Perks: 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 Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

About Nebius: 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. The Product In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. 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. The Role We are looking for a Senior Software Engineer to work on the content acquisition and crawling infrastructure of a novel search engine tailored for agentic AI consumption. In this role, you will focus on building systems that discover, fetch, and continuously refresh content from the open web and other large-scale data sources. You will design distributed crawling, scheduling, and ingestion infrastructure capable of operating at internet scale while balancing coverage, freshness, resource efficiency, and reliability. You will work on systems that process billions of URLs, manage high-throughput data flows, and ensure that high-quality content is consistently available to downstream indexing and retrieval systems. In this position, your responsibility will be to: Design, implement, and operate web-scale crawling systems for acquiring content from the internet Build ingestion workflows for internal and external data sources, including crawlers, structured feeds, and partner integrations Develop crawl scheduling, prioritisation, recrawl policies, and freshness strategies Build systems for URL discovery, deduplication, content extraction, and crawl orchestration Ensure reliable operation of crawling infrastructure under high-throughput conditions Define observability and quality metrics for crawl coverage, freshness, throughput, and content quality Monitor resource usage, bandwidth consumption, and infrastructure cost Collaborate with indexing and ML teams to ensure acquired content meets retrieval and ranking requirements Enable safe experimentation with crawling strategies and content acquisition policies You may be a good fit if you: 5+ years of experience building backend or distributed systems Strong Go or C++ expertise Experience with large-scale distributed systems (10k+ RPS, billions of URLs, high-throughput pipelines) Understanding of web protocols (HTTP, DNS, TLS), crawling, scraping, and content extraction Experience operating production systems and debugging failures in distributed environments Strong understanding of scalability, fault tolerance, and resource management Strong candidates may also have experience with: Web crawling Building streaming data pipelines and event-driven systems Kafka, Pulsar, NATS, RabbitMQ, or similar messaging platforms Designing distributed schedulers, queues, and asynchronous processing systems Spark, Flink, Beam, or MapReduce Ad tech, social networks, search engines, or other large-scale content platforms We conduct coding interviews as part of the process. Benefits & Perks: 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 Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

About Nebius: 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. The Product In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. 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. The Role We are looking for a Senior Software Engineer to work on the content acquisition and crawling infrastructure of a novel search engine tailored for agentic AI consumption. In this role, you will focus on building systems that discover, fetch, and continuously refresh content from the open web and other large-scale data sources. You will design distributed crawling, scheduling, and ingestion infrastructure capable of operating at internet scale while balancing coverage, freshness, resource efficiency, and reliability. You will work on systems that process billions of URLs, manage high-throughput data flows, and ensure that high-quality content is consistently available to downstream indexing and retrieval systems. In this position, your responsibility will be to: Design, implement, and operate web-scale crawling systems for acquiring content from the internet Build ingestion workflows for internal and external data sources, including crawlers, structured feeds, and partner integrations Develop crawl scheduling, prioritisation, recrawl policies, and freshness strategies Build systems for URL discovery, deduplication, content extraction, and crawl orchestration Ensure reliable operation of crawling infrastructure under high-throughput conditions Define observability and quality metrics for crawl coverage, freshness, throughput, and content quality Monitor resource usage, bandwidth consumption, and infrastructure cost Collaborate with indexing and ML teams to ensure acquired content meets retrieval and ranking requirements Enable safe experimentation with crawling strategies and content acquisition policies You may be a good fit if you: 5+ years of experience building backend or distributed systems Strong Go or C++ expertise Experience with large-scale distributed systems (10k+ RPS, billions of URLs, high-throughput pipelines) Understanding of web protocols (HTTP, DNS, TLS), crawling, scraping, and content extraction Experience operating production systems and debugging failures in distributed environments Strong understanding of scalability, fault tolerance, and resource management Strong candidates may also have experience with: Web crawling Building streaming data pipelines and event-driven systems Kafka, Pulsar, NATS, RabbitMQ, or similar messaging platforms Designing distributed schedulers, queues, and asynchronous processing systems Spark, Flink, Beam, or MapReduce Ad tech, social networks, search engines, or other large-scale content platforms We conduct coding interviews as part of the process. Benefits & Perks: 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 Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

About Nebius: 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. The Product In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. 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. The Role We are looking for a Senior Software Engineer to work on the content acquisition and crawling infrastructure of a novel search engine tailored for agentic AI consumption. In this role, you will focus on building systems that discover, fetch, and continuously refresh content from the open web and other large-scale data sources. You will design distributed crawling, scheduling, and ingestion infrastructure capable of operating at internet scale while balancing coverage, freshness, resource efficiency, and reliability. You will work on systems that process billions of URLs, manage high-throughput data flows, and ensure that high-quality content is consistently available to downstream indexing and retrieval systems. In this position, your responsibility will be to: Design, implement, and operate web-scale crawling systems for acquiring content from the internet Build ingestion workflows for internal and external data sources, including crawlers, structured feeds, and partner integrations Develop crawl scheduling, prioritisation, recrawl policies, and freshness strategies Build systems for URL discovery, deduplication, content extraction, and crawl orchestration Ensure reliable operation of crawling infrastructure under high-throughput conditions Define observability and quality metrics for crawl coverage, freshness, throughput, and content quality Monitor resource usage, bandwidth consumption, and infrastructure cost Collaborate with indexing and ML teams to ensure acquired content meets retrieval and ranking requirements Enable safe experimentation with crawling strategies and content acquisition policies You may be a good fit if you: 5+ years of experience building backend or distributed systems Strong Go or C++ expertise Experience with large-scale distributed systems (10k+ RPS, billions of URLs, high-throughput pipelines) Understanding of web protocols (HTTP, DNS, TLS), crawling, scraping, and content extraction Experience operating production systems and debugging failures in distributed environments Strong understanding of scalability, fault tolerance, and resource management Strong candidates may also have experience with: Web crawling Building streaming data pipelines and event-driven systems Kafka, Pulsar, NATS, RabbitMQ, or similar messaging platforms Designing distributed schedulers, queues, and asynchronous processing systems Spark, Flink, Beam, or MapReduce Ad tech, social networks, search engines, or other large-scale content platforms We conduct coding interviews as part of the process. Benefits & Perks: 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 Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.