AI Security Engineer

Job Title :AI Security Engineer
Location: REMOTE
Duration: Long Term Contract
Basic Qualifications
Professional software engineering experience building, deploying, and supporting enterprise or cloud-based applications.
Hands-on AI experience, including LLMs, generative AI applications, RAG architectures, AI agents, or intelligent automation solutions.
Bachelor's degree in Computer Science, Software Engineering, Information Systems, Cybersecurity, Artificial Intelligence, or a related technical discipline, or equivalent practical experience.
Programming experience in Python, JavaScript, Go, Java, or similar modern languages.
Familiarity with APIs, cloud platforms, containers, CI/CD pipelines, and Git-based development workflows.
Basic understanding of secure coding principles, application security concepts, and common software vulnerabilities.
Strong analytical, troubleshooting, and problem-solving skills.
Effective written and verbal communication skills with the ability to work across technical and non-technical teams.
Ability to work a flexible schedule when required to support production deployments, operational incidents, maintenance activities, or on-call rotations.
Demonstrated willingness to continuously learn, evaluate, and adopt emerging technologies, AI frameworks, security tools, cloud services, and engineering platforms.
Ability to adapt to changing business priorities, project requirements, and technology environments while maintaining high-quality delivery standards.

Preferred Qualifications
Experience developing AI-powered applications or automation solutions in development, testing, or production environments.
Exposure to application security, cybersecurity engineering, vulnerability management, DevSecOps, or secure software development practices.
Familiarity with AI security concepts including prompt injection, data leakage, model misuse, and access controls.
Experience with AI frameworks and platforms such as OpenAI, Azure AI, Anthropic, LangChain, LangGraph, Semantic Kernel, LlamaIndex, or similar technologies.
Familiarity with vector databases, AI evaluation techniques, and retrieval-augmented generation (RAG) architectures.
Working knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (Google Cloud Platform).
Experience using GitHub Copilot, Cursor, Windsurf, VS Code Agent, or other AI-assisted engineering tools.
Demonstrated curiosity and initiative in learning new technologies and applying automation to improve engineering productivity.
Experience working in agile environments with rapidly evolving technologies, business priorities, and engineering requirements.
Education
Bachelor's degree in Computer Science, Software Engineering, Cybersecurity, Artificial Intelligence, Data Science, Information Systems, or a related technical field.
Master's degree in Computer Science, Artificial Intelligence, Cybersecurity, or a related discipline is preferred but not required.
Relevant certifications are desirable and may include:
Microsoft Azure AI Engineer Associate
AWS Certified Developer Associate
Google Associate Cloud Engineer
CompTIA Security+
Certified Secure Software Lifecycle Professional (CSSLP)
GIAC Security Certifications
Generative AI, Machine Learning, or AI Engineering certifications from recognized providers