[Hiring] Senior Cybersecurity Engineer @Phia LLC

Role Description

phia is hiring a Senior Cybersecurity Engineer (Cloud Security) to support cyber defense engineering and operations at a large Federal agency. This role will provide technical expertise for hybrid, multi-cloud environments, focusing on security configuration hardening, integration, and automation, to protect assets, data, and identity. These efforts will enable proactive threat & fraud detection and mitigation, and continuous policy compliance assessment.

This position offers REMOTE work flexibility, while primary customer locations include the Fairfax, VA and Raleigh, NC areas. Qualified candidates must be U.S. Citizens and located in the United States. The position requires Public Trust security vetting approval.

What You’ll Do

• Security Posture & Compliance Automation: Design and implement automated compliance assessments to enforce hardening standards (CIS, NIST) across cloud accounts and on-premises virtualized environments.
• Asset & Data Security: Architect and maintain the security of our sprawling asset inventory. Implement data-at-rest and data-in-transit encryption strategies that span from physical data center servers to cloud-native storage.
• Identity & Fraud Mitigation: Develop and secure the "Identity Fabric" linking 600k+ employees and millions of commercial customers. Collaborate with Fraud teams to integrate signals from SIEM and Databricks to detect and block malicious account activity.
• Hybrid Engineering: Build and manage secure connectivity (Transit Gateways, Service Mesh) between on-premises hypervisors and multi-cloud environments, ensuring consistent policy enforcement.
• Threat Detection & Response: Partner with the SOC to develop high-fidelity detection logic. Build SOAR playbooks that automate the isolation of compromised cloud workloads or on-premises VMs.
• Efficacy Assessment: Support ongoing "Purple Team" exercises and control testing to validate that security tools (EDR, WAF, DLP) are performing as intended across all tenants.
• AI/ML Security Governance (Adversarial Defense): Establish security guardrails for the enterprise’s internal and customer-facing AI models. This includes protecting Databricks training pipelines from data poisoning and implementing mitigations for LLM-specific threats like prompt injection and sensitive data leakage.
• Hyper-Automation of Security Operations: Drive the transition from manual "click-to-operate" security to Autonomous Security Operations. This involves building advanced SOAR playbooks that use ML-based triggers to perform auto-remediation across hybrid environments without human intervention.
• Business Process Streamlining: Partner with business units to integrate security "invisibly" into their workflows. Use automation to reduce "security friction" in logistics and retail operations, ensuring that compliance checks (like PCI or SOC2) are performed continuously and programmatically.
• AI Asset Management: Discover and catalog "Shadow AI" usage across the enterprise, ensuring all third-party AI tools meet the enterprise’s privacy and security standards. Communicate findings and insights clearly to technical and business stakeholders.

Qualifications

• Expert-level knowledge of security architectures in AWS, Azure, and Google Cloud.
• Mastery of Terraform, Ansible, or CloudFormation to deploy and manage security configurations at massive scale.
• Ability to leverage Databricks to perform deep-dive analysis on billions of logs for threat hunting and efficacy reporting.
• Experience securing Kubernetes (EKS/AKS/GKE) and Docker environments, focusing on runtime protection and image integrity.
• Proficiency with OAuth 2.0, SAML, and CIAM solutions for large-scale customer and employee authentication.
• Proficiency in using Python (PySpark/Pandas) within Databricks to build custom anomaly detection models that go beyond standard SIEM correlation rules.
• Knowledge of the OWASP Top 10 for LLMs and experience implementing AI gateways or "firewalls" to monitor and filter AI-generated traffic.
• Deep expertise in building "glue code" that connects disparate COTS and custom applications via secure, automated APIs to streamline cross-functional business activities.
• The ability to explain to non-technical stakeholders how AI-driven security decisions are made and how to handle "false positives" at scale.
• A relentless focus on identifying repetitive manual tasks and replacing them with self-healing, automated systems.

Requirements

• Bachelor’s and/or Master’s degree preferred, but can be substituted with significant experience.
• 8+ years of relevant experience (cybersecurity architecture & engineering).
• 4+ years focused on large-scale cloud or hybrid environments.

Preferred Skills

• Demonstrated AI or Machine Learning expertise applied to solve security or operational scaling problems.
• Demonstrated experience managing environments with 10,000+ workloads and high-availability requirements for retail/commercial applications.
• Experience with Databricks and Splunk (cloud data integration, analytics, etc.).

Certifications (preferred)

• Certified Information Systems Security Professional (CISSP)
• Certified Cloud Security Professional (CCSP)
• GIAC Public Cloud Security (GPCS)
• GIAC Cloud Security Automation (GCSA)
• Amazon Web Services (AWS) Certified Security – Specialty
• Google Professional Cloud Security Engineer
• Microsoft Certified: Azure Security Engineer Associate

Security Clearance/Vetting

• U.S. Citizenship required
• Ability to complete Public Trust vetting