Requirements

8+ years of experience as a software engineer working on production backend systems
Strong hands-on expertise in C++ or Rust in real-world, high-load services
Experience building and operating high-load, low-latency user-facing systems handling thousands of requests per second under strict latency constraints
Deep understanding of performance at a systems level including CPU, memory, networking, and data access
Experience operating own code in production, including deploying, debugging incidents, and rolling back changes
Thinking end-to-end about request flows rather than isolated components
Ability to balance correctness, latency, and development velocity with pragmatic tradeoffs
Strong collaboration and communication skills across engineering, ML, and product teams

Nice to Haves

Experience with DBMS internals (open source or SaaS) and cloud infrastructure
Experience with high-load web applications or large-scale APIs
Experience with performance-critical systems such as trading platforms or real-time data pipelines
Low-level performance tuning and hardware-level optimisation skills
Open-source contributions or active involvement in the engineering community
Competitive programming or CTF participation
Participation in SHAD or similar advanced technical programmes
Conference talks or technical publications

Design, implement, and operate core runtime services for serving search queries at scale
Build and optimise request flows including query processing, retrieval orchestration, and response assembly under strict latency budgets
Develop systems that maintain performance and predictability under high load
Optimise CPU, memory, and data access patterns in performance-critical paths
Ensure reliability, observability, and predictability across production services
Build well-tested systems with clear responsibilities and interaction contracts, maintaining flexibility as architecture evolves
Define and implement observability primitives like structured logs, metrics, traces, and latency breakdowns
Monitor throughput, latency, and resource usage and drive improvements in performance and cost efficiency
Collaborate with indexing and ML teams to integrate retrieval and ranking components with decoupled ML logic
Support experimentation and iteration through controlled rollouts and rigorous benchmarking