Job Title
AI/ML Security Architect and Engineer
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Job Description
We are seeking a highly skilled and motivated AI Security Architect/Engineer to join our growing security team. In this role, you will design, develop, and deploy AI-driven solutions to detect, prevent, and respond to cyber threats and 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.
Key Responsibilities:
* Architect and implement scalable Generative AI features, including agentic workflows, conversational AI, and autonomous agents.
* Develop and deploy machine learning models for threat detection, anomaly detection, malware classification, and behavioral 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.
* Analyze 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.
* Ensure compliance with data privacy regulations (e.g., GDPR, HIPAA) and AI governance frameworks.
* Ensure AI systems are explainable, auditable, and aligned with ethical and regulatory standards.
Requirements:
* 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.
* Be an Australian Citizen.
Preferred 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 (highly desirable).
* 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).
* Excellent problem-solving and communication skills.
Work at the intersection of machine learning, data science, and security engineering to build intelligent systems that enhance our security posture.