Cyber Security Engineer

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 discover 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 Dev Sec Ops  and SOC workflows.

• 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
• 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
• Identity exposure (human and non‑human identities)
• Data sensitivity and regulatory impact

• Security frameworks, standards and best practices for prioritization and risk assessment

• 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

• LLMs, RAG pipelines, AI agents, and copilots
• Implement protections against prompt injection, data exfiltration, adversarial attacks, AI model integrity risk and related threats
• Build and enforce AI guardrails and runtime controls
• Establish data protection and governance practices

• Embed AI‑driven security controls across CI/CD pipelines and MLOps workflows
• 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

• Bachelor’s or Master’s degree in Computer Science, Cybersecurity or a 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 modelling
• Security tools: SAST, DAST, SCA, SIEM, SOAR, CNAPP, CSPM
• Zero‑Trust architecture, IAM/PAM, network security

• 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 of Java, Go, C# (etc.)
• Experience writing 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