About the company
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter.
Responsibilities
- Contributing to core performance engineering initiatives from development to production, focusing on the delivery of impactful optimizations.
- Executing technical designs and plans for architectural and code-level performance improvements.
- Implementing foundational performance models and methodologies for complex, distributed systems.
- Supporting optimization strategies to ensure Elasticsearch remains performant, predictable, and scalable in diverse environments.
- Profiling and analyzing system behavior to identify bottlenecks in logging, metrics, vector search, and ES|QL.
- Ensuring robust performance benchmarks and regression detection for both stateful and stateless (Serverless) architectures.
- Collaborating with peers across the team to apply performance-focused development practices into new features.
- Contributing to automation efforts by building AI-assisted optimization harnesses that streamline profiling, hypothesis testing, and benchmarking.
- Providing technical guidance and peer reviews to other engineers, fostering a culture of technical excellence.
Requirements
- Deep knowledge of Java internals and JVM memory management.
- Understanding of concurrency models, high-performance, thread-safe, and lock-free code.
- Experience with large open-source and enterprise codebases.
- Proven experience in profiling and optimizing distributed systems, including benchmarking tools (e.g., JMH, Rally), identifying performance regressions, and implementing algorithmic or hardware-aware optimizations.
- Solid comprehension of distributed systems architecture, including partition tolerance, cluster state propagation, and scaling challenges in large-scale data stores.
- Proven track record of using AI or advanced tooling to accelerate optimization, debug complex performance issues, and automate benchmarking workflows.
- Ability to collaborate effectively within a team environment.
- Ability to work autonomously, drive decisions, and result in a distributed team by leveraging asynchronous, direct, and transparent communication.
Conditions
- Compensation for this role is in the form of base salary. This role does not have a variable compensation component.
- The typical starting salary range for new hires in this role is $128,300 — $203,000 CAD.
- In addition to cash compensation, this role is currently eligible to participate in Elastic's stock program.
- Total rewards package includes a company-matched Registered Retirement Savings Plan (RRSP) with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits.