AI Engineer — Security | Remote

We are actively seeking an experienced and specialized AI Engineer — Security to join our technology team on a full-time, remote basis. In this critical cybersecurity leadership role, you will be responsible for securing cutting-edge artificial intelligence, Large Language Models (LLMs), and generative AI pipelines against evolving threat vectors. You will architect robust AI guardrails, conduct advanced prompt injection and jailbreak testing, and enforce rigorous cloud and MLOps security standards.

This opportunity requires a skilled engineering professional with deep expertise in AI/LLM security, Python programming, and enterprise Dev Sec Ops  frameworks.

As an AI Engineer — Security, you will take full ownership of designing, implementing, and auditing comprehensive security controls for artificial intelligence and machine learning applications. Your day-to-day responsibilities include performing threat modeling, executing red teaming simulations against LLMs, validating compliance with OWASP Top 10 for LLM applications, and securing cloud infrastructure across AWS, Azure, and GCP. You will collaborate closely with AI research, data science, and platform engineering teams to integrate security into CI/CD pipelines, manage API authentication and secrets, and deploy automated monitoring using SIEM/SOAR platforms like Splunk and Azure Sentinel.

Furthermore, you will prevent data leakage and ensure adherence to data privacy regulations.

• Design, implement, and maintain advanced security architectures for artificial intelligence, machine learning, and LLM systems.
• Conduct comprehensive prompt injection, jailbreak testing, and adversarial red teaming simulations against generative AI models.
• Enforce compliance with the OWASP Top 10 for LLM Applications and enterprise cybersecurity standards.
• Perform thorough AI/ML threat modeling and risk assessments across model training and inference pipelines.
• Secure cloud-native environments across AWS, Azure, and GCP, focusing on IAM, secrets management, and API security.
• Integrate automated security testing, vulnerability scanning, and code analysis into MLOps and CI/CD pipelines (Dev Sec Ops ).
• Configure and manage SIEM and SOAR platforms (Splunk, Microsoft Sentinel) for real-time AI security monitoring and incident response.
• Deploy robust AI guardrails, content filtering, and Data Leakage Prevention (DLP) mechanisms using Lang Chain, Hugging Face, Tensor Flow, and PyTorch.

• Minimum of 5+ years of professional experience in software engineering, cybersecurity, or application security roles.
• Proven specialization and hands-on experience in AI/LLM Security, generative AI threat analysis, and secure MLOps.
• Extensive programming and scripting expertise in Python.
• Practical mastery of prompt injection testing, jailbreak mitigation, and LLM red teaming methodologies.
• Deep working knowledge of the OWASP Top 10 for LLM Applications and standard enterprise security frameworks.
• Strong technical expertise in cloud security (AWS, Azure, or GCP), IAM policies, secrets management, and API security.
• Experience integrating security tools into CI/CD pipelines and Dev Sec Ops  workflows.
• Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or a related technical discipline.

• Professional cybersecurity certifications such as CISSP, OSCP, AWS Certified Security – Specialty, or CCSP.
• Hands-on experience with AI orchestration and ML frameworks including Lang Chain, Hugging Face Transformers, Tensor Flow, and PyTorch.
• Familiarity with vector databases, embedding security, and specialized LLM firewalls (e.g., NeMo Guardrails, Llama Guard).
• Prior working experience securing AI-driven enterprise products or SaaS platforms.
• Contributions to open-source security tools or published research in AI/ML safety and security.

Salary/Rate:
Market Competitive / Standard

Deadline:
Open until filled

Notice Period:
Immediate to 30 Days

Contract Duration:
Permanent / Full-Time Remote