AI Cyber Engineer

Ampcus Inc; Chantilly (VA); On-site; USD 120,000 - 160,000; Full time

Job summary

Ampcus Inc is looking for an AI Cyber Engineer in Chantilly, VA. This senior role focuses on implementing AI-driven security capabilities to detect and fix vulnerabilities across IT environments. Candidates should have strong experience in cybersecurity, software engineering, and AI systems, along with various required certifications.

The engineer will design automated vulnerability detection pipelines and strategies while collaborating with cross-functional teams to enhance security across all platforms.

Qualifications

• 8+ years in cybersecurity or software engineering.
• 3+ years working with AI/ML systems or AI security.
• Security certifications (CISSP, OSCP, etc.) are required.

Responsibilities

• Design and deploy AI-powered vulnerability discovery pipelines.
• Build AI models for risk prioritization.
• Develop automated patching pipelines and IaC remediation templates.

Skills

Vulnerability management

Penetration testing

Threat modeling

AI security risks

Programming in Python

Education

Bachelor’s or Master’s degree in Computer Science or Cybersecurity

Tools

AWS security services

SIEM

Terraform

Job description

Job Title

AI Cyber Engineer

Location

Chantilly, VA

Job Summary

The AI Cyber Engineer is a senior technical role responsible for implementing and operating AI-driven cybersecurity capabilities to continuously detect, prioritize, and remediate vulnerabilities across the enterprise IT environment. This role combines cybersecurity engineering, artificial intelligence, software development, and automation to move beyond traditional reactive security into proactive and autonomous remediation. The engineer will leverage advanced AI models, agentic frameworks, and security tooling to:

• Continuously identify vulnerabilities across infrastructure, applications, and AI systems.
• Generate prioritized remediation strategies.
• Automatically develop fixes where feasible (e.g., patches, configuration updates, code changes).
• Integrate findings into enterprise DevSecOps and SOC workflows.

Key Responsibilities

• AI-Driven Vulnerability Detection & Analysis
  • Design and deploy AI-powered vulnerability discovery pipelines across cloud, on-prem infrastructure, applications, APIs, microservices, and AI/LLM systems.
  • Leverage AI techniques for pattern recognition in logs, telemetry, and attack signals; behavioral anomaly detection; identification of zero‑day and emerging threats.
  • Perform AI‑assisted attack simulation and adversarial testing to proactively identify weaknesses.
• Intelligent Risk Prioritization
  • Build AI models and scoring mechanisms to correlate vulnerabilities with threat intelligence, exploitability, and business impact while reducing false positives.
  • Incorporate asset criticality, identity exposure, data sensitivity, and regulatory impact into risk evaluation.
  • Align prioritization with frameworks such as NIST CSF/AI RMF and MITRE Telecommunication&CK/ATLAS.
• Automated & Assisted Remediation
  • Develop and maintain automated patching pipelines, IaC remediation templates, and secure‑code transformation scripts.
  • Build AI agents to perform repeatable, permissible tasks.
  • Collaborate with engineering teams for safe deployment of automated remediation.
• Secure AI & Application Ecosystem Engineering
  • Secure enterprise AI systems, including LLMs, RAG pipelines, AI agents, and copilots.
  • Implement protections against prompt injection, data exfiltration, adversarial attacks, AI model integrity risk, and more.
  • Build and enforce AI guardrails, secure model deployment pipelines, data protection, and governance practices.
• DevSecOps & Continuous Security Integration
  • Embed AI-driven security controls across CI/CD and MLOps workflows.
  • Implement shift-left security scanning, automated policy enforcement, and continuous compliance monitoring.
  • Detect and remediate vulnerabilities pre‑production before release.
• Cross-Functional Collaboration
  • Work closely with AI Program, Cloud Platform & Engineering, Software Engineering, Security Operations, and GRC teams.
  • Translate security findings into developer-friendly remediation actions and guide secure coding practices.

Required Qualifications

• Education & Experience
  • Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or related field.
  • 8+ years in cybersecurity, software engineering, or cloud security.
  • 3+ years working with AI/ML systems or AI security.
  • Security certifications (CISSP, OSCP, CCSP, AWS Security Specialty, etc.).
• Technical Skills
  • Vulnerability management, penetration testing, threat modeling.
  • Security tools: SAST, DAST, SCA, SIEM, SOAR, CNAPP, CSPM.
  • Zero‑Trust architecture, IAM/PAM, network security.
  • Experience with MITRE Telecommunication&CK/ATLAS, NIST AI Risk Management Framework, AI & Emerging Security.
  • AI & model fundamentals and AI security risks.
  • Experience with LLMs, RAG, agentic AI systems, autonomous agents or multi‑agent AI systems.
  • Experience configuring AI‑driven security tools or platforms.
• Software Engineering & Automation
  • Programming: Python (required), plus Java, Go, C#, etc.
  • Secure code, automation scripts, IaC (Terraform, etc.).
  • Generate or validate automated code fixes.
• Cloud & Infrastructure
  • AWS, Azure, GCP security services.
  • Containers and Kubernetes security.
  • API security and microservices architecture.
• Key Competencies
  • Strong problem‑solving, systems thinking, and ability to translate security issues into practical solutions.
  • Deep curiosity about emerging threats and AI capabilities.
  • Balance between automation and risk control.
  • Excellent communication with technical and non‑technical stakeholders.

Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.