Cybersecurity Engineer

Atlas is seeking a mid-senior cybersecurity engineer based in Rahway, NJ (hybrid) to apply AI and ML across detection, remediation, DevSecOps, identity, and automation. The role includes piloting safe AI integrations and mentoring the team to advance security program maturity.

Responsibilities

• Evaluate current detection, response, DevSecOps, identity, and automation initiatives; identify pragmatic AI opportunities that can retrofit into live programs.
• Prioritize and execute AI pilots that deliver rapid, measurable cyber value; document outcomes, safety controls, and scalable runbooks for expansion.
• Develop AI-enabled detection and triage capabilities that fuse CrowdStrike telemetry with Microsoft Sentinel data to reduce analyst workload and improve prioritization.
• Augment existing SOAR and ServiceNow runbooks with AI-assisted enrichment and decisioning while preserving human oversight and audit trails.
• Strengthen DevSecOps by introducing AI-assisted IaC checks, secure IaC templates (Terraform), and GitHub Actions automations to prevent misconfigurations.
• Advance Zero Trust and identity engineering with AI to highlight risky access patterns and propose refinements to conditional access (Zscaler, Azure AD).
• Produce production-ready engineering artifacts such as Terraform modules, Sentinel analytics, ServiceNow runbooks, GitHub Action snippets, and test harnesses that integrate with existing processes.
• Coach and mentor team members through internal knowledge sharing, playbooks, pair-programming, and ongoing support for AI features.
• Maintain rigorous model governance and security controls for AI use, including data lineage, access controls, monitoring, explainability, test datasets, and rollback procedures.
• Measure and report security outcomes, including MTTR, detection accuracy, analyst time saved, incident volume changes, and coverage improvements.
• Advocate for pragmatic AI adoption within the organization, balancing innovation with safety, compliance, and operational sustainability.

Requirements

• 5 to 10 years of hands-on cybersecurity engineering experience delivering production solutions across detection, automation, DevSecOps, identity, or endpoints.
• Proven ability to introduce and integrate AI and ML into live security programs with measurable improvements.
• Strong Terraform and GitHub Actions expertise for IaC and pipeline security; capable of producing reusable modules and CI integrations.
• Operational experience with CrowdStrike telemetry and Microsoft Sentinel analytics and playbooks.
• Experience building ServiceNow and SOAR automations and integrating runbooks with detection tooling.
• Familiarity with Zero Trust controls, including Zscaler and Azure AD conditional access.
• Production scripting or programming skills (Python preferred) and experience deploying automation to live environments with rollback and auditability.
• Strong communicator and collaborator, adept at mentoring less-experienced teammates and creating clear documentation and training artifacts.
• Systems thinker with a pragmatic, risk-based approach to prioritization and delivery.

Technologies

• Terraform
• GitHub Actions
• CrowdStrike
• Microsoft Sentinel
• Zscaler
• Azure AD
• ServiceNow

CATALYZE AI ADOPTION

• Bring forward-thinking, practical AI engineering into existing security programs to reduce risk faster and increase team effectiveness.
• Demonstrate measurable wins by pilots that the team can operationalize and scale, such as reduced MTTR and higher coverage.
• Lower adoption friction by producing reusable artifacts, runbooks, and training that enable sustainable AI integrations within the current team.
• Ensure responsible AI adoption through model governance, human-in-the-loop controls, and clear rollback and audit procedures.