Elasticsearch Engineer

Job Title: Elasticsearch Engineer - (CANDIDATE ALREADY SELECTED)

Work Hours: Core Business Hours (8 am 5 pm)
Site: 100% Remote, California

U.S. citizenship is required. We do not provide sponsorship.

Position Summary
We are seeking an experienced Elasticsearch Engineer to design, build, optimize, and support highly scalable search and analytics solutions. The ideal candidate has deep expertise in the Elastic Stack (Elasticsearch, Kibana, Logstash, Beats, and Elastic Agent), distributed systems, data indexing strategies, and search relevance tuning. This role partners with software engineering, DevOps, data engineering, and business stakeholders to deliver high-performance search capabilities and observability platforms.

Key Responsibilities
Design, implement, and maintain Elasticsearch clusters in production environments.
Develop scalable indexing pipelines for structured and unstructured data.
Optimize search performance, query execution, and cluster health.
Design index mappings, analyzers, tokenizers, and search relevance models.
Collaborate with application developers to integrate Elasticsearch APIs and optimize application search functionality.
Document architecture, operational procedures, and best practices.

Required Qualifications
Bachelor\'s degree in Computer Science, Information Systems, Engineering, or equivalent experience.
5%2B years of software engineering or infrastructure engineering experience.
3%2B years of hands-on Elasticsearch administration and development experience.
Strong understanding of distributed systems and search technologies.
Experience designing Elasticsearch clusters for high availability and fault tolerance.
Proficiency with:
Elasticsearch
Kibana
Logstash
Experience with REST APIs and Elasticsearch Query DSL.
Strong knowledge of:
Index mappings
Sharding and replication
Index Lifecycle Management (ILM)
Snapshot and restore
Cluster monitoring

Preferred Qualifications
Experience operating Elasticsearch clusters with millions of documents.
Knowledge of vector search, semantic search, and AI-powered retrieval.
Experience implementing observability solutions using the Elastic Stack.
Experience with Linux system administration.
Familiarity with Docker and Kubernetes.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Proficiency in scripting using Python, Bash, or PowerShell. Elastic Certified Engineer certification is a plus.

Technical Skills
Search Technologies
Elasticsearch
Search relevance tuning

Elastic Stack
Kibana
Logstash
Elastic Agent

Cloud & Infrastructure
AWS
Azure
Google Cloud Platform
Kubernetes
Docker

Programming
Python
Java
JavaScript
Bash
PowerShell
.NET

Databases
SQL
Data modeling
ETL pipelines

Monitoring
Kibana
Elastic Observability

Desired Competencies
Strong analytical and problem-solving skills.
Excellent troubleshooting abilities.
Experience working in Agile development environments.
Strong communication and collaboration skills.
Ability to balance performance, scalability, and operational simplicity.
Attention to detail and commitment to operational excellence.

Nice-to-have experience
Vector databases and hybrid search
Retrieval-Augmented Generation (RAG)
Embedding models
Machine Learning for ranking and recommendations
Elastic Search AI Assistant
Observability and Security features within the Elastic Stack

Start Time: Core Business Hours (8 am 5 pm)
End Time: Core Business Hours (8 am 5 pm)