Introduction
A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat. Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
Your Role And Responsibilities
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. You will work at the intersection of machine learning, data science, and security engineering to build intelligent systems that enhance our security posture.
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 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.
* 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.
Required Technical And Professional 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.
* Be an Australian Citizen
Preferred Technical And Professional 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.