Agentic AI Engineer III - Cybersecurity

About the role

Joining Amex Tech means discovering and shaping your contribution to something big. Here, you can work alongside talented tech teams and build a unique career with the Powerful Backing of American Express.

Responsibilities

• Design and implement LLM-powered and agentic AI solutions that automate cloud security, governance, and operational workflows.
• Build and extend agentic AI workflows capable of reasoning over enterprise security context, invoking cloud security tools, and performing automated actions with appropriate guardrails and human oversight.
• Develop AI agents that integrate with enterprise cloud platforms, SaaS applications, identity services, CNAPP, CSPM, SSPM, SIEM, and security orchestration platforms.
• Design and maintain Retrieval-Augmented Generation (RAG) pipelines using enterprise security documentation, cloud architecture, policies, incident data, and operational knowledge while ensuring correctness, privacy, and regulatory compliance.
• Develop Security-as-Code and Policy-as-Code capabilities that enable AI agents to validate cloud configurations, enforce security guardrails, and recommend or automate remediation activities.
• Contribute to shared AI infrastructure including LLM services, orchestration frameworks, vector databases, agent evaluation frameworks, and AI observability tooling.
• Build AI-powered automation for cloud security assessments, threat modeling, security posture analysis, compliance validation, and risk reporting.
• Participate in operating AI systems in production, including monitoring model performance, evaluating agent behavior, debugging issues, improving reliability, and ensuring secure AI operations.
• Collaborate with cloud engineering, cybersecurity, platform engineering, product, and business teams to translate security and operational requirements into scalable AI-enabled solutions.
• Ensure AI systems are designed with enterprise security, governance, explainability, auditability, and responsible AI principles.

Qualifications

• 2+ years of professional software engineering experience.
• Solid engineering fundamentals in at least one backend language (Python, Go, or TypeScript).
• Familiarity with APIs, basic cloud concepts, and modern development practices.
• Interest in agentic AI systems, autonomy, and AI-assisted development workflows.
• Willingness to learn, take feedback, and grow technical ownership over time.
• Comfort working in collaborative, cross-functional teams.
• A strong customer mindset and curiosity about real-world problem solving.

Preferred Qualifications

• Exposure to LLM tooling, prompt engineering, RAG, or agent frameworks through work, coursework, or personal projects.
• Internship or early-career experience in fintech or other regulated environments.
• Contributions to open-source projects, hackathons, or side projects related to AI or developer tooling.

Pay

Ultimately, in determining your pay, we’ll consider your location, experience, and other job-related factors.