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

Nice to Haves:

• 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

What You'll Be Doing:

• 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 nearline pipelines
• Monitor throughput, resource usage, and cost, and drive optimizations 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

Perks and 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