Principal Software Engineer II (Performance Team)

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. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

We are seeking a Principal Software Engineer II to join our Elasticsearch Performance Engineering area. This role will set the technical direction for our automated benchmarking tools. Youll define methodologies, architecture and design for testing Elasticsearch ingest and search workloads at cloud scale, including identifying performance regressions

RESPONSIBILITIES

• Design and building of tooling and automated processes for provisioning and execution of Elasticsearch performance benchmarking jobs at scale.

• Defining methodologies and guidelines for performance benchmarking servicing development teams and solution architects.

• Play a lead role in cross-functional team efforts and engagements.

• Mentoring and advising team members on proposed technical solutions.

• Developing reporting for and interpreting of benchmarking results.

• Investigate and assist in resolving performance escalations and capacity planning issues.

• Address and devise solutions for benchmarking disparate use cases and workloads

QUALIFICATIONS

• Software development experience with Python and Linux shell required (Expert Level).

• Familiarity with Linux system-level performance measurement and associated tooling (for example: how to measure and compare CPU, memory, and disk I/O performance between cloud provider instance types).

• Prior experience in the troubleshooting and root cause analysis of performance issues in complex distributed architectures.

• Prior experience with CI/CD pipelines and automating process workflows.

• Experience in cloud architectures, service models, and operating across multiple cloud service providers, assessing tradeoffs from both performance and deployment perspectives.

• Ability to multitask, effectively manage your time, and collaborate with team members globally across time zones.

• Familiarity with measuring performance and sizing in Linux VM and container environments.

• Experience with performance tuning of Java applications and JVMs

BONUS POINTS

• Prior experience with large, distributed search engines and in developing and tuning queries.

• Familiarity with the Elasticsearch Query API and building Kibana dashboards is a strong plus.

• Cloud orchestration with Kubernetes.

• Experience applying the use of Artificial Intelligence (AI) for devising and expanding benchmarking practices and enhancing benchmarking tooling