Senior Elastic Engineer (TS​/SCI w​/CI Poly Required

Trusted Connectivity for AI-Powered Dominance. Everfox delivers trusted connectivity to protect the world’s most critical environments and safeguard the sensitive data powering decision advantage. Built for mission-critical operations, Everfox protects what matters most by securing how data moves, how users access it, and how threats are neutralized across every domain. We enable mission speed and secure collaboration across networks, domains, and allies, while ensuring the data powering AI and advanced analytics remains trusted and protected.

We don’t just defend systems; we deliver decision dominance.

Our Purpose. Protect what matters most by enabling organizations to operate security in the most complex and high-risk digital environments.

Our Vision. To be the most trusted authority in high-assurance cybersecurity, enabling secure collaboration across every domain.

Our Belief. Security should never limit mission success - it should enable it.

Our Promise. We deliver absolute confidence in environments where failure is not an option.

About the Role We are seeking an experienced Senior Elasticsearch Engineer to design, develop, optimize, and maintain enterprise-scale search platforms powered by the Elastic Stack. The ideal candidate will have deep expertise in Elasticsearch architecture, indexing strategies, query optimization, cluster administration, and observability solutions. You will collaborate with software engineers, data engineers, and Dev Ops teams to build highly available, scalable search solutions that support mission-critical applications.

Location:

Chantilly, VA

• Design, implement, and maintain highly available Elasticsearch clusters.
• Develop efficient indexing strategies for structured and unstructured data.
• Optimize search performance, relevance scoring, and query execution.
• Monitor cluster health and troubleshoot performance bottlenecks.
• Configure and maintain Elastic Stack components including:
  Elasticsearch Kibana Logstash Beats Elastic Agent
• Implement Index Lifecycle Management (ILM), snapshots, backups, and disaster recovery strategies.
• Design mappings, analyzers, tokenizers, and ingest pipelines.
• Build dashboards and visualizations using Kibana.
• Work with development teams to integrate Elasticsearch APIs into applications.
• Perform cluster upgrades, scaling, and capacity planning.
• Implement security using Elastic Security, RBAC, TLS, and authentication mechanisms.
• Automate deployments using Infrastructure as Code (Terraform, Ansible, Helm, or similar).
• Support production incidents and perform root cause analysis.

• Installing, configuring, and scaling Elasticsearch nodes and indices.

• Integrating database audit logs, alert logs, and OS metrics into the ELK Stack (Elasticsearch, Logstash, Kibana).

• Mapping definitions, query optimization, and shard/replica management for fast text-based analytics.

• Monitoring cluster health, JVM heap tuning, and resolving node dropouts or lag issues.

• Vector & Semantic Search:
  Experience with dense vector fields, embeddings, and hybrid ranking (Reciprocal Rank Fusion) using the Elasticsearch Relevance Engine.
• Machine Learning Integration:
  Familiarity with Learning to Rank (LTR), integrating third-party transformer models
• Cloud & Orchestration:
  Hands-on practice with Elastic Cloud (ECE/ESS), Kubernetes operators, or AWS-managed deployments
• Advanced Operations:
  Skills in Cross-Cluster Replication (CCR), cross-cluster search, and custom Painless scripting for complex data streams.

• An active (currently in use) - TS/SCI with CI Polygraph
• A bachelor’s degree in computer science, Information…