AI Engineer - Cybersecurity

Bachelor's degree

Computer Science, Cybersecurity, Engineering, Information Technology, Artificial Intelligence, Machine Learning, Data Science, or related technical field.

3+ years of technical experience directly related to cybersecurity domains.

3+ years of experience writing production-level code in Python; ReactJS and modern AI frameworks is highly preferred.

1+ years of experience building tools with large language models, AI/ML systems, automation, or agentic AI frameworks.

Deep knowledge of large language model operations, prompt engineering, context management, retrieval patterns, and how modern AI agents operate.

Experience coding with agentic frameworks such as LangChain, AutoGen, Semantic Kernel, CrewAI, or similar libraries to build custom multi-agent systems.

Experience designing, deploying, and securing AI agents using Amazon Bedrock AgentCore capabilities such as Runtime, Memory, Gateway, Identity, and Observability to support production-grade agentic workflows.

Broad understanding of core security principles spanning Identity and Access Management, Application Security, Cloud Security, Governance, Risk, Compliance, and Security Operations.

Understanding of AI-specific risks such as prompt injection, data leakage, data poisoning, model misuse, tool misuse, unauthorized shadow AI, and unsafe automated actions.

Understanding of how diverse systems interact, including identity providers, CI/CD pipelines, SIEMs, cloud platforms, vulnerability management tools, ticketing systems, and APIs.

Skill in writing programmatic safety mechanisms, enforcing least-privilege access within code, and building human-in-the-loop fallback workflows.

Knowledge of secure software development practices including code review, testing, dependency management, threat modeling, logging, monitoring, and production release controls.

Ability to translate cybersecurity requirements into scalable AI-enabled workflows, reusable components, technical documentation, and engineering playbooks.

Ability to work independently and self-motivate. Excellent problem solving, critical thinking, interpersonal, collaboration, written and verbal communication skills.

What will help you propel from the pack (Preferred Qualifications):

Master's Degree

Computer Science, Cybersecurity, Artificial Intelligence, Machine Learning, secure software engineering, or related technical field.

Demonstrated experience designing and deploying production-grade AI-enabled cybersecurity solutions at enterprise scale.

Experience leading the technical design of reusable agentic workflows, secure integrations, or multi-agent systems across multiple cybersecurity domains.

Experience with open-source agentic frameworks such as LangChain, AutoGen, Semantic Kernel, CrewAI, or similar orchestration tools.

Experience building or securing large language model applications, retrieval-augmented generation pipelines, AI agents, API integrations, or AI-enabled cybersecurity workflows.

CRISC, CEH, GIAC Family, or equivalent cybersecurity certification

AI, cloud, or secure software development certifications are preferred.

Knowledge of AI security standards and guidance such as OWASP Top 10 for LLM Applications, NIST AI RMF, or similar guidance.

Experience with ReactJS and modern AI frameworks.

Experience programming in Go, JavaScript, or TypeScript.

Hands-on experience with Amazon Bedrock AgentCore or a comparable managed enterprise agent platform.