Senior Engineer, Competitive Benchmarking & Performance
Elastic · United States
About this role
## Elastic — Senior Engineer, Competitive Benchmarking & Performance Elastic, the Search AI Company, enables everyone to find answers in real time using all their data at scale. Elastic’s Search AI Platform is used by more than 50% of the Fortune 500 and brings together search precision and AI intelligence for search, security, and observability. ### What is the Role Elasticsearch powers search, observability, and AI retrieval (RAG) for the world’s largest organizations. We’re seeking a **Senior Software Engineer** to lead **competitive benchmarking** initiatives within the **Elasticsearch Performance** team. This is a hands-on engineering role focused on building benchmarks and investigating performance, with technical publishing as a shared responsibility alongside engineering and content partners. ### What You Will Be Doing - Own prioritized competitive benchmarking initiatives across **search**, **vector & hybrid retrieval**, and **analytical & observability** workloads. - Build and maintain automated benchmark harnesses, datasets, query sets, and load profiles that reflect real-world usage (including concurrent ingestion and querying). - Design fair comparisons with documented system versions, configurations, tuning decisions, resource budgets, and functional differences. - Evaluate **latency distributions**, **throughput**, **resource consumption**, and **cost efficiency** (and measure retrieval performance at comparable recall/relevance targets). - Adapt and extend workload-appropriate tools such as **Elasticsearch Rally**, **ClickBench**, and vector search benchmark frameworks. - Investigate performance differences using profiling, system metrics, and controlled experiments; collaborate with engineering teams to identify causes and validate improvements. - Evaluate self-managed and managed cloud deployments, including serverless offerings, accounting for scaling behavior and service constraints. - Publish reproducible benchmark artifacts and clear technical reports explaining methodology, findings, limitations, and tradeoffs. - Partner with engineering and product management to prioritize benchmark coverage and translate findings into actionable product improvements. ### What You Bring - Solid software engineering skills; experience building maintainable automation and analysis tools in **Python** (or another relevant language). - Hands-on experience evaluating and diagnosing performance in **distributed systems**, **databases**, or **search infrastructure**. - Depth in at least one relevant area (search, vector retrieval, analytical databases, or observability) and the ability to learn unfamiliar systems. - Experience designing representative datasets and workloads (query patterns, concurrency, ingestion behavior). - Sound experimental judgment: repeated measurements, variability analysis, warm-up/cache effects, and distinguishing meaningful changes from measurement noise. - Experience building reproducible test environments and documenting configurations, procedures, and results. - Clear technical writing and communication skills. - Strong collaboration skills and the ability to turn performance evidence into engineering recommendations. ### Bonus Points - Experience with **Elasticsearch**, **Lucene**, **Rally**, **ClickBench**, or vector search benchmark frameworks. - Experience measuring retrieval quality alongside latency/throughput/resource usage. - Familiarity with cloud performance and cost analysis (autoscaling, s
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