Chief AI Security Strategist

2 weeks ago

Canberra, ACT, Australia beBeeSecurity Full time $63,700 - $190,000
AI/ML Security Architect and Engineer Job Description

This role involves designing, developing, and deploying AI-driven solutions to detect, prevent, and respond to cyber threats.

Key Responsibilities:

  • Develop scalable Generative AI features including agentic workflows, conversational AI, and autonomous agents.
  • Create and deploy machine learning models for threat detection, anomaly detection, malware classification, and behavioural analysis.
  • Apply best practices in AI security, including mitigation of hallucinations, prompt injection, and bias.
  • Identify and mitigate risks related to adversarial machine learning, model inversion, data poisoning, and prompt injection.
  • Analyse large-scale security datasets (e.g., logs, network traffic, endpoint telemetry) to identify patterns and build predictive models.
  • Research and implement AI and Machine Learning techniques to improve detection accuracy and reduce false positives.
  • Design and implement security controls for AI/ML systems, including model training, inference, and data pipelines.
  • Collaborate with security analysts and incident response teams to integrate AI tools into existing workflows.
  • Work with data scientists, ML engineers, and DevOps teams to integrate security into the AI/ML lifecycle.
  • Build automation pipelines for data preprocessing, model training, evaluation, and deployment.
  • Monitor model performance and retrain models as needed to adapt to evolving threats.
  • Stay current with emerging threats, vulnerabilities, and research in AI security and adversarial machine learning.
  • Ensure compliance with data privacy regulations and AI governance frameworks.
Requirements
  • Familiarity with full AI project lifecycle from research and prototyping to deployment in production environments.
  • Experience with Agile development methodologies.
  • Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, or similar.
  • Background in AI and/or data governance.
  • Knowledge of AI ethics, fairness, and explainability.
  • Strong understanding of cybersecurity principles, threat landscapes, and common attack vectors.
  • Experience with threat modeling and securing cloud-based AI infrastructure.
  • Background in data engineering and working with large-scale datasets.

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