Elastic5 days ago

Principal Software Engineer - Performance Tuning - Elasticsearch

RUB 13,317–21,067per month · before tax

MARKET

11,962 ₽median for this role

QA Performance / Load · 12 jobs with disclosed pay

5,583half of the offers: 8,225–109,344369,400

At market · above 67% of offers

United States

Responsibilities

01Owning core performance engineering initiatives from architecture to production, focusing on the delivery of high-impact optimizations
02Leading the technical design, plan, and execution for major architectural and code-level performance improvements
03Developing foundational performance models and methodologies for complex, distributed systems
04Driving optimization strategies to ensure Elasticsearch remains performant, predictable, and scalable in diverse environments
05Profiling and analyzing system behavior to identify bottlenecks in logging, metrics, vector search, and ES|QL
06Ensuring robust performance benchmarks and regression detection for both stateful and stateless (Serverless) architectures
07Collaborating across the company to embed performance-first thinking into new features from the outset
08Drive automation efforts by designing and building AI-assisted optimization harnesses that streamline profiling, hypothesis testing, and benchmarking
09Mentoring and coaching other engineers, fostering a culture of technical excellence and performance-aware development

01Deep knowledge of Java internals and JVM memory management
02Understanding of how concurrency models work
03Ability to write code that is high-performance, thread-safe, and lock-free
04Experience working with large open-source and enterprise codebases
05Proven experience in profiling and optimizing distributed systems
06Deep experience with benchmarking tools (e.g., flamegraphs, JMH, Rally), identifying performance regressions, and implementing algorithmic or hardware-aware optimizations
07Solid comprehension of distributed systems architecture, including partition tolerance, cluster state propagation, and scaling challenges in large-scale data stores
08Proven track record of using AI or advanced tooling to accelerate optimization, debug complex performance issues, and automate benchmarking workflows
09Ability to collaborate across functions and teams, acting as a force multiplier for performance engineering across the organization
10Ability to collaborate across functions and teams and seamlessly transition between different projects, codebases, or teams based on business priorities
11Ability to work autonomously, drive decisions and result in a distributed team by leveraging asynchronous, direct, and transparent communication

01Compensation for this role is in the form of base salary
02This role does not have a variable compensation component
03The typical starting salary range for new hires in this role is listed below
04In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below
05These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting
06We may ultimately pay more or less than the posted range, and the ranges may be modified in the future
07An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs
08Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders
09Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program
10Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being