AI Security Engineer

As an AI Security Engineer, you will work at the intersection of software engineering, cybersecurity, and artificial intelligence. You will design and build security tools, assess AI-powered applications for vulnerabilities, evaluate third-party and open-source AI technologies, and help establish secure development standards for AI systems.

This is a hands-on engineering role for someone who enjoys building solutions, solving complex technical problems, and exploring emerging security risks across technologies such as Generative AI, RAG, and agentic systems.

What You'll Do

• Design, build, and implement tools for AI security testing, penetration testing, red teaming, and continuous vulnerability assessment.
• Develop mock and test AI applications to evaluate internal and third-party AI security solutions.
• Identify and assess security risks within AI-enabled applications and workflows.
• Develop security requirements, standards, and best practices for securely building and deploying AI applications.
• Evaluate third-party vendors, open-source tools, libraries, and AI technologies from a security perspective.
• Integrate security testing and evaluation capabilities into CI/CD pipelines and development workflows.
• Build scalable security tooling and automation that can be adopted across different teams and environments.
• Troubleshoot applications and solve complex engineering and security problems.
• Partner with engineering teams, security professionals, customers, vendors, and business stakeholders to understand requirements and deliver practical solutions.
• Create clear technical documentation covering tools, features, security assessments, testing methodologies, and findings.

What You'll Bring

• 5+ years of software development experience building and supporting production applications.
• Strong hands-on programming experience with Python.
• Experience working with RESTful APIs and structured data formats such as JSON, XML, CSV, and HTML.
• Experience with CI/CD pipelines and modern software development practices.
• Strong Linux and scripting skills.
• Experience troubleshooting and supporting production applications.
• Understanding of core application security concepts, including authentication, authorization, encryption, secrets management, and secure development practices.
• Experience with Microsoft Azure, including foundational cloud networking and security concepts.
• Understanding of modern AI application architectures, including Retrieval-Augmented Generation (RAG), LLM-based applications, and agentic systems.