Senior Elasticsearch Engineer

Swarmint•Bethesda, MD

8d•$200,000•Onsite

About The Position

We're seeking a Senior Elasticsearch Engineer to architect and optimize search infrastructure for a large-scale enterprise data solution supporting our Intelligence Community customer. You'll design systems that enable real-time search and retrieval across petabytes of data to support operational intelligence analysis and decision-making. This role requires regular on-site work at customer facilities in Bethesda, Maryland, including work in classified facilities (SCIF).

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
8-12 years experience with Elasticsearch in production environments
Deep understanding of search engine internals, indexing, and query optimization
Experience designing and scaling distributed search clusters
Strong programming and scripting skills for automation and tooling
Experience building data ingestion pipelines
Proficiency with cluster monitoring and performance analysis
Understanding of distributed systems and data replication
Active TS/SCI with Single Scope (CI) Polygraph Required (Do not apply unless you have this)
U.S. Citizenship required
Ability to work on-site in Bethesda, Maryland 2-4 days/week including at classified facilities

Nice To Haves

Experience with vector search and similarity queries
Knowledge of OpenSearch or experience with multiple search platforms
Familiarity with AI/ML workflows and embedding-based search
Experience with streaming data platforms and message queues
Knowledge of data lakehouse architectures and technologies
Experience with complementary data stores and caching systems
Understanding of workflow orchestration tools
Experience with containerization technologies (Docker)
Knowledge of government data systems and security requirements (NIST 800-171, CMMC)
Experience in air-gapped or restricted environments
Experience with enterprise-scale data solutions at petabyte scale

Responsibilities

Design and implement high-performance search infrastructure for large-scale data ingestion and retrieval
Architect indexing strategies for diverse data types including time-series, geospatial, and vector embeddings
Build and optimize real-time data pipelines for continuous index population
Performance tune queries and clusters for sub-second response times on massive datasets
Integrate search capabilities with AI/ML pipelines and analytics platforms
Design data retention, archival, and lifecycle management strategies
Deploy and manage search infrastructure in containerized environments and on-premises deployments
Work in restricted and air-gapped network environments
Mentor engineers on search architecture and optimization techniques
Collaborate across teams on data architecture and integration patterns