Cyber Security Architect

Defining and maintaining security standards, guidelines, and methodologies for AI-enabled applications, LLM-based systems, AI agents, and automation tools. • Assessing AI use cases for risks such as data leakage, prompt injections, insecure plugins, excessive permissions, model misuse, and exposure of sensitive information. • Reviewing applications, cloud, API, and AI solution architectures from a security perspective. • Supporting secure implementation of AI and non-AI applications throughout the SSDLC. • Defining practical AI security controls aligned with industry best practices, responsible AI principles, and emerging AI security standards. • Working with development and infrastructure teams to identify, prioritize, and remediate security risks. • Providing hands-on security guidance, secure design recommendations, and remediation plans. • Evaluating risks related to prompts, outputs, embeddings, training data, AI-generated content, and third-party AI solutions.

• 2–3+ years of experience in application security, product security, DevSecOps, or secure software engineering. • Strong understanding of AI security risks in LLMs, AI-enabled applications, AI agents, and data-driven systems. • Solid understanding of SSDLC, DevSecOps practices, and security testing tools such as SAST, DAST, SCA, and secrets scanning. • Experience with one or more programming languages such as Python, Java, .NET, JavaScript, C, or similar. • Familiarity with modern application architectures, including APIs, microservices, containers, serverless, and cloud environments. • Knowledge of common security frameworks and best practices such as OWASP Top 10, OWASP LLM Top 10, NIST, and secure-by-design principles. • Strong analytical, troubleshooting, and problem-solving skills. • Excellent communication skills, including the ability to explain technical risks to both technical and non-technical stakeholders. • Proactive, detail-oriented, and eager to learn new technologies and security domains.