About the Company:
Our client is building a next-generation search infrastructure product for AI agents: an external, paid search API that enables agents and AI applications to retrieve fresh, relevant, and hard-to-find information from the web.
The product is being built as a large-scale search system consisting of several core layers: web crawling, offline indexing and document processing, ML-based ranking, and high-load runtime serving.
The Runtime team owns the online serving layer: the performance-critical service that receives search queries, retrieves relevant documents from a massive corpus, ranks them, selects the best results, and returns them through an external API.
This is a greenfield infrastructure challenge at search-engine scale, with a small but very senior engineering team and a strong focus on deep systems engineering, performance, latency, and cost efficiency.
The product is being built as a large-scale search system consisting of several core layers: web crawling, offline indexing and document processing, ML-based ranking, and high-load runtime serving.
The Runtime team owns the online serving layer: the performance-critical service that receives search queries, retrieves relevant documents from a massive corpus, ranks them, selects the best results, and returns them through an external API.
This is a greenfield infrastructure challenge at search-engine scale, with a small but very senior engineering team and a strong focus on deep systems engineering, performance, latency, and cost efficiency.
Key Responsibilities:
- Design and build the high-load runtime serving layer of a search engine for AI agents.
- Develop performance-critical C++ components responsible for query processing, retrieval, ranking, result selection, and response serving.
- Work on systems that must handle very high throughput and strict latency requirements.
- Profile and optimize CPU usage, memory usage, allocations, concurrency, network, IO, serialization, cache behavior, and other low-level bottlenecks.
- Make architecture and implementation decisions that balance latency, throughput, reliability, and infrastructure cost.
- Collaborate with engineers working on crawling, indexing, offline processing, and ML ranking to build an end-to-end search pipeline.
- Build core infrastructure rather than simply integrating existing tools or assembling ready-made services.
- Contribute to the technical direction of the Runtime layer in a highly senior, hands-on engineering environment.
Requirements:
- Strong hands-on C++ engineering experience and seniority level: Staff / Principal / Tech Lead / Google L6+ equivalent.
- Experience building high-load, low-latency, performance-critical systems.
- Deep understanding of systems internals, performance optimization, profiling, and debugging.
- Proven personal ownership of components that handled significant production load, ideally tens of thousands of RPS, thousands of RPS per node, or hundreds of thousands of RPS at service level.
- Ability to explain concrete performance bottlenecks you identified and fixed, including trade-offs around latency, throughput, memory, CPU, and cost.
- Experience working on internals of complex systems, not only integrating ready-made infrastructure such as Kafka, Redis, Elasticsearch, or databases.
- Relevant backgrounds in search engines, recommendation systems, feed ranking, databases, storage engines, query engines, advertising infrastructure, high-frequency trading, low-latency systems, or large-scale distributed infrastructure.
Employment Terms:
- Senior / Staff / Principal-level role in a small, highly experienced engineering team.
- BigTech-level compensation, with the possibility of a strong equity component.
- Relocation is preferred for candidates who are not already in one of the company’s office locations (New York, London, Amsterdam, Tel Aviv).
- Remote work from Europe or the US East Coast can be considered.
- Other remote locations may be considered for exceptional candidates with unique expertise.
Send your CV on Telegram @bkvirn