AI Security Specialist

7 days ago

Canberra, ACT, Australia beBeeSecurity Full time $63,700 - $200,000

A career in technology consulting involves developing long-term relationships and collaborating closely with clients worldwide.

Your Role And Responsibilities

We seek a highly skilled AI Security Architect/Engineer to join our security team. In this role, you will design, develop, and deploy AI-driven solutions to detect and prevent cyber threats. You will be responsible for securing AI/ML systems, models, and data pipelines against adversarial threats, ensuring compliance with security best practices, and collaborating with cross-functional teams to build robust, trustworthy AI solutions.

  • Architect and implement scalable Generative AI features, including conversational AI and autonomous agents.
  • Develop 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.
  • Collaborate 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.
Required Technical Expertise

Experience in full AI project lifecycle, from research and prototyping to deployment in production environments. Familiarity with Agile development methodologies. Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, or similar. Experience with AI and/or data governance. Experience with building automation solutions with AI/ML. 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 (e.g., AWS, Azure, GCP). Experience with data engineering and working with large-scale datasets.

Preferred Technical Experience

Experience with Ansible, Red Hat OpenShift, Kubernates and CI/CD Pipelines. Experience with secure MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker). Experience with LangChain, OpenAI APIs, or similar LLM frameworks. Knowledge of RAG (Retrieval-Augmented Generation), vector databases, and custom embeddings. Experience with vector DB's or open file formats like parquet, avro or orc. Familiarity with cloud platforms (AWS, Azure, GCP) and security tools (SIEM, EDR, IDS/IPS).

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