Cyber AI Specialist

As a Cyber AI Specialist, your primary responsibilities will include integrating AI solutions into our cybersecurity framework, automating penetration testing, and collaborating with the DevSecOps team to embed AI functionalities in CI/CD pipelines. You'll develop and deploy AI/ML models for cyber threat detection and work on analyzing datasets to preempt vulnerabilities. Staying updated on emerging threats and ethical AI standards will also be essential.

To be a successful candidate for the Cyber AI Specialist role, you will need a Bachelor’s or Master’s degree in Computer Science, Cybersecurity, AI or a related field, alongside a solid 3+ years of experience in AI/ML development or cybersecurity. Proficiency in programming languages like Python or Java and familiarity with tools and frameworks such as TensorFlow or PyTorch are also vital.

A Cyber AI Specialist should possess strong AI/ML expertise, along with a solid understanding of cybersecurity principles. Key technical skills include experience with machine learning frameworks, knowledge of deep learning and NLP, plus the ability to find and mitigate vulnerabilities in AI models. Familiarity with security tools and cloud platforms is also important.

Our Cyber AI Specialist will enjoy a comprehensive benefit package that includes meal and parking allowances, full salary and benefits during probation, family health insurance, career development opportunities, and a balanced work-life schedule of 40 hours per week from Monday to Friday, including additional leave days.

We prioritize the growth of our Cyber AI Specialists through various initiatives such as technical seminars, industry conferences, and mentoring from experienced professionals. We also host internal hackathons and company events to encourage collaboration and innovation among our teams.

When integrating AI into a cybersecurity framework, it's essential to first assess the existing security measures in place. Then, I would identify the areas where AI could provide the most value, such as automating threat detection or improving incident response times. Collaborating with team members to ensure that the AI models are aligned with the overall security strategy is key.

I have hands-on experience with both TensorFlow and PyTorch, utilizing these frameworks to develop and implement machine learning models. For example, I previously used TensorFlow to train a neural network for anomaly detection in network traffic, optimizing it for real-time applications.

Staying current with cyber threats and AI advancements is a priority for me. I regularly read industry publications, attend relevant conferences, and participate in online forums. Additionally, I take part in webinars and training courses to deepen my knowledge and share insights with my peers.

To ensure the security and ethics of AI models, I would conduct regular security audits and risk assessments, analyze any biases in training data, and implement adversarial training techniques. Collaboration with ethics teams to align models with societal values is also crucial.

In my previous role, I discovered a vulnerability during a penetration test where an outdated library was being used in the application. I reported the issue and worked with the development team to patch the vulnerability, demonstrating the importance of proactive security measures.

I would leverage AI for threat detection by developing machine learning models trained on historical attack data, enabling them to recognize patterns and anomalies indicative of potential threats. Additionally, deploying these models in real-time systems would enhance our ability to detect and respond to incidents swiftly.

In my role, I collaborated closely with DevSecOps teams to build secure CI/CD pipelines by integrating AI tools for security checks. This allowed us to automate vulnerability scanning and improve the overall security posture of our deployment processes.

The biggest challenge in securing AI systems is the potential for adversarial attacks, where malicious actors might manipulate input data to deceive the models. Addressing this requires constant vigilance, robust training methodologies, and a thorough understanding of potential attack vectors.

When explaining complex AI concepts to non-technical stakeholders, I focus on breaking down the information into simple terms and relatable analogies. I find it helpful to use visuals and real-world examples to illustrate how AI impacts our security efforts and why it matters.

I believe my strong foundation in both AI and cybersecurity, along with my passion for continuous learning and problem-solving, makes me a great fit for the Cyber AI Specialist position. I'm excited about the opportunity to contribute to enhancing security measures in the banking industry.