Job description

Dragonfli Group is a cybersecurity and IT consulting firm headquartered in Washington, DC, delivering strategic solutions to government agencies and enterprise clients nationwide. We specialize in designing, building, and securing advanced technology solutions, integrating AI/ML into cybersecurity operations, and protecting organizations from sophisticated threats. Our teams operate in diverse work environments—including on-site, hybrid, and fully remote—on contracts ranging from several months to multiple years. We are seeking an Architect/Engineer – Cybersecurity Solutions to lead the design, integration, and optimization of AI/ML-powered security capabilities. This role combines technical engineering expertise, solution architecture, and AI/ML security integration to address evolving threat landscapes. The ideal candidate will have a deep technical foundation in cybersecurity, experience in AI system security, and the ability to operationalize secure, compliant, and high-performing solutions across enterprise environments. Key Responsibilities: • Lead the integration and management of AI/ML technologies into security solutions to detect, prevent, and respond to advanced cyber threats. • Oversee and ensure compliance with AI-related security policies, secure development lifecycles, and vulnerability management processes. • Conduct cybersecurity risk assessments, audits, program development, and incident response exercises involving AI systems. • Establish secure development environments for AI platforms and integrated tools. • Collaborate with AI/ML developers, security architects, legal, and business stakeholders to operationalize AI security strategies and comply with emerging legislation. • Develop and deliver AI security training programs to raise awareness of risks and mitigation techniques. • Perform threat modeling and risk assessments to identify vulnerabilities and recommend mitigation strategies. • Design and implement security solutions such as DLP, SIEM, and endpoint monitoring to support insider threat detection and telemetry ingestion. • Create and maintain security blueprints, principles, and standards to ensure secure, scalable IT architecture. • Tune and optimize detection systems to reduce false positives and adapt to evolving behaviors and environments. • Support secure deployment of behavioral analytics models with privacy and governance compliance. • Engineer automated response capabilities for insider risk detection, including alerting and access control actions. Benefits: Benefits: • Insurance – health, dental, and vision • Paid Time Off (PTO) and 11 Federal Holidays • 401(k) employer match Requirements: Required Skills & Qualifications: • Bachelor’s degree in computer science, information security, or related field. • Deep understanding of AI/ML concepts, implementation, and security. • Strong technical foundation in network security, operating systems (Windows, Linux, UNIX), cloud computing (AWS, Azure), TCP/IP, cryptography, and database security. • Proficiency in system integration, API security, log forwarding, and automation (Python, PowerShell, Bash). • Knowledge of network architecture, endpoint telemetry, and insider risk detection in hybrid environments. • Understanding of cyber threats, attack vectors, vulnerabilities, and security frameworks (NIST, ISO 27001). • Strong communication skills to convey complex security concepts to technical and non-technical audiences. • Awareness of legal and ethical considerations in insider monitoring and AI/ML deployment. Preferred Qualifications: • Expertise in mitigating AI-specific vulnerabilities such as adversarial attacks, model poisoning, prompt injection, bias detection, and privacy risks. • Experience with cloud-native security architectures in AWS, Azure, and Google Cloud. • Certifications in AI security, governance, or development. Travel: Minimal, as required for project activities. Clearance Requirement: U.S. citizenship or lawful permanent residency required. AI Usage Policy: Candidates must be able to independently demonstrate technical proficiency without the use of AI tools during interviews or performance assessments.

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