AI Solutions Engineer at Essex Solutions in Atlanta, GA

Job description

• The AI Portfolio & Cybersecurity Engineer manages and coordinates the organization’s AI portfolio while supporting the design, implementation, and governance of AI and LLM-based solutions. The role also strengthens the organization’s cybersecurity capabilities by engineering security tools and assisting with vulnerability management, incident response, and GRC activities. Its purpose is to help translate AI opportunities into secure, governed, and measurable business solutions while improving the organization’s overall cyber resilience.

Responsibilities

• Manage and maintain the enterprise AI portfolio, including proposed, approved, pilot, active, and completed initiatives.
• Coordinate the AI business-use-case intake, evaluation, prioritization, approval, and project lifecycle processes.
• Track AI project schedules, milestones, dependencies, risks, resource needs, costs, benefits, and value realization.
• Prepare AI portfolio dashboards, status reports, metrics, and executive-level updates.
• Partner with business units, IT, cybersecurity, Legal, HR, and other stakeholders to translate business needs into secure AI solutions.
• Assist IT and technical teams with designing, building, testing, integrating, and deploying AI and large language model (LLM) solutions.
• Evaluate AI platforms, models, vendors, and technical architectures for security, functionality, scalability, and business fit.
• Apply AI governance requirements related to data protection, privacy, acceptable use, human oversight, model risk, and regulatory compliance.
• Engineer, install, configure, integrate, maintain, and troubleshoot cybersecurity tools and supporting technologies.
• Develop automation, integrations, and AI-assisted workflows that improve cybersecurity operations and organizational efficiency.
• Support vulnerability management activities, including scanning, analysis, risk prioritization, remediation coordination, validation, and reporting.
• Assist with cybersecurity incident response, including investigation, containment, evidence collection, documentation, recovery, and post-incident review.
• Support governance, risk, and compliance activities, including risk assessments, control evaluations, audits, policy development, and evidence collection.
• Monitor emerging AI technologies, cybersecurity threats, vulnerabilities, regulations, and industry practices.
• Develop technical documentation, implementation procedures, user guidance, and knowledge-transfer materials.
• Promote the secure and responsible adoption of AI through stakeholder consultation, training, and ongoing support.
• Perform other cybersecurity engineering and operational responsibilities as assigned based on organizational priorities.

Requirements

• Bachelor’s degree in Cybersecurity, Information Technology, Computer Science, Engineering, Data Science, or a related field, or equivalent combination of education, certifications, and relevant experience.
• Three to five years of experience in cybersecurity, IT engineering, AI solutions, systems administration, or a related technical role.
• Experience implementing, configuring, integrating, or supporting cybersecurity technologies and enterprise IT systems.
• Working knowledge of AI technologies, large language models, automation, APIs, cloud platforms, and secure solution-development practices.
• Experience supporting projects or portfolios, including requirements gathering, status tracking, risk management, stakeholder coordination, and executive reporting.
• Practical experience in one or more cybersecurity disciplines, such as vulnerability management, incident response, security operations, or governance, risk, and compliance.
• Familiarity with cybersecurity and AI governance frameworks, regulatory requirements, and data-protection principles.
• Relevant certifications—such as Security+, CySA+, SSCP, CISSP Associate, cloud, project management, or AI-related credentials—are preferred but not required.

Skills

Required

• AI technologies
• Large language models
• Automation
• APIs
• Cloud platforms
• Secure solution-development practices
• Cybersecurity technologies
• Enterprise IT systems
• Vulnerability management
• Incident response
• Security operations
• Governance, risk, and compliance