Ampcus IncRemote
Cyber Security Engineer
United States of America
Full Time
1 hour ago
H1B Sponsor Likely
Key skills
AI-driven cybersecurityVulnerability managementPenetration testingThreat modelingSASTDASTSCASIEMSOARCNAPPCSPMZero Trust architectureIAMPAMNetwork securityMITRE ATT&CKNIST AI Risk Management FrameworkAI security risksLLMsRAG pipelinesAgentic AI systemsAutonomous agentsPython programmingJava programmingGo programmingC# programmingSecure codingAutomation scriptingInfrastructure as CodeTerraformAWS security servicesAzure security servicesGCP security servicesContainers securityKubernetes securityAPI securityMicroservices architectureSecurity certifications CISSPSecurity certifications OSCPSecurity certifications CCSPSecurity certifications AWS Security SpecialtySystems thinkingPythonJavaC#CGoAIMLLLMRAGAgenticMLOpsAWSAzureGCPKubernetesCI/CDRisk ManagementCommunicationPenetration TestingNetwork SecurityCloud SecurityZero Trust
About this role
Ampcus Inc is seeking a Cyber Security Engineer for a senior technical role responsible for implementing and operating AI-driven cybersecurity capabilities. The engineer will leverage AI to detect vulnerabilities, prioritize remediation strategies, and integrate findings into enterprise workflows.
Responsibilities:
- Design and deploy AI-powered vulnerability discovery pipelines across:
- Cloud (AWS, Azure, GCP)
- On-prem infrastructure
- Applications, APIs, and microservices
- AI/LLM systems and data pipelines
- 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
- Leverage and build-on AI models and scoring mechanisms to:
- Correlate vulnerabilities with threat intelligence, exploitability, and business impact
- Reduce false positives and alert fatigue
- Implement contextual risk evaluation incorporating:
- Asset criticality
- Identity exposure (human and non-human identities)
- Data sensitivity and regulatory impact
- Align prioritization with frameworks such as:
- NIST CSF/AI RMF
- MITRE ATT&CK/ATLAS
- Develop and maintain:
- Automated patching pipelines
- Infrastructure-as-Code (IaC) remediation templates
- Secure code transformation scripts (e.g., Python, Java, Terraform)
- Build AI agents to perform repeatable, permissible tasks
- Collaborate with engineering teams to ensure safe deployment of automated remediation
- 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 and runtime controls
- Secure model deployment pipelines
- Data protection and governance practices
- Embed AI-driven security controls across:
- CI/CD pipelines and MLOps workflows
- Implement:
- Shift-left security scanning and validation
- Automated policy enforcement
- Continuous compliance monitoring
- Ensure vulnerabilities are automatically:
- Detected pre-production and remediated (or blocked) before release
- Work closely with:
- AI Program teams
- Cloud Platform and Cloud Engineering teams
- Software engineering teams
- Security operations and GRC teams
- Translate security findings into developer-friendly remediation actions
- Provide guidance on secure coding and vulnerability remediation
Requirements:
- 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 (e.g., CISSP, OSCP, CCSP, AWS Security Specialty)
- Vulnerability management, penetration testing, threat modeling
- Security tools: SAST, DAST, SCA, SIEM, SOAR, CNAPP, CSPM
- Zero Trust architecture, IAM/PAM, network security
- Experience applying: MITRE ATT&CK/ATLAS
- NIST AI Risk Management Framework
- AI and model fundamentals
- AI security risks
- Experience with LLMs, RAG, and agentic AI systems
- Experience with autonomous agents or multi-agent AI systems
- Experience configuring and using AI-driven security tools or platforms
- Programming: Python (required), plus one or more (Java, Go, C#, etc.)
- Experience writing: Secure code, Automation scripts, Infrastructure as Code (Terraform, etc.)
- Experience generating or validating automated code fixes
- AWS, Azure, and/or GCP security services
- Containers and Kubernetes security
- API security and microservices architecture
- Strong problem-solving and systems thinking
- 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 both technical and non-technical stakeholders