Security Engineer, AI
$80,000–$120,000 year
Remote
Job Summary
Evaluate and assess the security posture of Large Language Models and generative AI systems, conducting threat modeling and security architecture reviews for AI/ML data pipelines. Implement and maintain security controls for model training, fine-tuning, and inference infrastructure, while developing baselines and hardening configurations for AI platforms. Identify and remediate vulnerabilities specific to AI/ML systems, including prompt injection and model poisoning, alongside implementing data privacy controls for training datasets. Develop security runbooks for incident response and contribute to internal policies, proof-of-concept builds, and training on AI risks. Work remotely from North America with a starting salary of $80,000 - $120,000.
Required Qualifications
- Has the ability to work from an Applied Systems office or 100% remotely
- Minimum of 3-5 years' experience in security engineering or DevSecOps roles
- Demonstrated foundational understanding of machine learning concepts, ML workflows, and common frameworks (PyTorch, TensorFlow, scikit-learn)
- Working knowledge of Large Language Models, transformer architectures, and generative AI applications
- Experience with or strong understanding of LLM security concerns (prompt injection, jailbreaking, data poisoning, model extraction)
- Experience with container security, Kubernetes security, and securing AI workloads in containers
- Knowledge of cloud security in AI contexts (GPU security, distributed training security, data protection in ML pipelines)
- Understanding of secure software development practices and supply chain security as applied to ML models
- Knowledge of model governance, versioning, and secure model deployment
- Experience with infrastructure-as-code technologies (Terraform, Ansible)
- Experience with one or more scripting languages (Python, Bash, Go)
- Understanding of encryption, key management, and data privacy (especially PII in training data)
- Familiarity with vulnerability scanning and secure code practices
- Working knowledge of compliance frameworks and their application to AI systems (GDPR, SOC 2, etc.)
- Experience with securing data pipelines and ETL processes
- Excellent written and verbal communication skills
- Demonstrated ability to work independently and as part of a team
- Willingness to rapidly learn new AI technologies and security frameworks
- Candidate will need to reside in North America
Desired Qualifications
- Certification in security (Security+, CISSP, etc.)
- Experience with specific LLM platforms (OpenAI API, Anthropic Claude, Google Vertex AI, Azure OpenAI)
- Experience with ML security tools and platforms (Robust Intelligence, Arthur AI, etc.)
- Participation in AI security research, publications, or conferences
- Experience in threat modeling for AI systems
- Background in security research or penetration testing
- Experience with red-teaming AI systems
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