Elasticsearch Engineer; Secret Clearance

Elasticsearch Engineer (Secret Clearance)

ShorePoint is a fast-growing, industry recognized and award-winning cybersecurity services firm with a focus on high-profile, high-threat, private and public-sector customers who demand experience and proven security models to protect their data. ShorePoint subscribes to a "work hard, play hard" mentality and celebrates individual and company successes. We are passionate about our mission and going above and beyond to deliver for our customers.

We are equally passionate about an environment that supports creativity, accountability, diversity, inclusion and a focus on giving back to our community.

We are seeking an Elasticsearch Engineer (Secret Clearance) with expertise in designing, deploying and optimizing Elastic Stack solutions in federal environments. This role supports the delivery of Elastic-based solutions across cloud, on-prem and hybrid infrastructures to enable security operations and data-driven outcomes. The Elasticsearch Engineer will lead technical implementations, support migrations and contribute to scalable architectures while engaging directly with client stakeholders.

This is a unique opportunity to shape the growth, development and culture of an exciting and fast-growing company in the cybersecurity market.

What you'll be doing:

• Architect, deploy and tune Elastic Stack solutions (Elastic Cloud Enterprise (ECE), Elastic Cloud on Kubernetes (ECK), Elastic Cloud) across cloud, on-prem and hybrid environments.
• Execute legacy security platform migrations, including detection translation (e.g., Search Processing Language (SPL) → (ES|QL) Elasticsearch Query Language) and analyst workflow modernization.
• Design and implement data ingestion pipelines using Elastic Agent, Fleet, Logstash and Beats.
• Harden deployments for federal compliance, including Transport Layer Security (TLS), Personal Identity Verification/Common Access Card (PIV/CAC), Single Sign-On (SSO) / Security Assertion Markup Language (SSO/SAML), Security Technical Implementation Guide (STIG) and audit logging.
• Build outcome-driven dashboards and advanced Kibana visualizations.
• Develop automation using Infrastructure-as-Code (IaC) tools (Ansible, Terraform or equivalent).
• Communicate technical decisions and trade-offs directly to client stakeholders.
• Contribute to internal IP, including reusable templates, automation and reference architectures.

What you need to know:

• Deep understanding of Elastic Stack capabilities and use cases across deployment, security and operations.
• Knowledge of distributed cluster architecture at scale, including multi-tenant and CCS environments.

Must have's:

• 6+ years in systems engineering or infrastructure, including 2+ years of production Elastic Stack experience.
• Proven ability to analyze complex requirements and translate them into clear, actionable tasks and processes through critical thinking.
• Strong problem-solving skills and a self-starter mentality.
• Solid written and verbal communication skills.
• Linux Command-Line Interface (CLI) fundamentals and basic networking knowledge.
• Hands-on experience with containerization and IaC tooling.
• Proficiency with at least one major cloud provider.
• Experience with federal security controls (TLS, SSO/SAML, PIV/CAC, STIG).
• Proven track record leading engagements from scoping through delivery.
• Deep knowledge of distributed cluster architecture at scale, including multi-tenant and CCS environments.
• Ability to drive client relationships and identify expansion opportunities.
• Applicants must currently hold and maintain an active Secret clearance.

Beneficial to have:

• Bachelor's degree in Cybersecurity, Computer Science, Information Technology, Engineering or a related field.
• Elastic certifications (ECE or being on a defined certification track).
• Elastic Security (SIEM, detection engineering, threat hunting and legacy migration).
• Detection translation experience (SPL → ES|QL or equivalent).
• Scripting proficiency (Python, Bash or Power Shell).
• Exposure to AI-augmented search, RAG or semantic search use cases.
• Prior professional services or consulting experience.

Where it's done:

• Onsite (Huntsville, AL or Colorado Springs, CO or Orlando, FL or Virginia Beach, VA).