Security Engineer AI
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Key skills for this role
About the Role
Capital.com is seeking an AI Security Engineer to secure AI-driven systems including LLM applications and ML models. The role involves designing security controls, threat modeling, and mitigating AI-specific threats.
Key Skills for This Role
Responsibilities
- Design and implement security controls for AI/ML systems across development, training, and production
- Secure LLM integrations, RAG pipelines, and AI APIs
- Conduct threat modeling for AI systems and data pipelines
- Identify and mitigate AI specific threats: prompt injection, model poisoning, adversarial attacks, etc.
- Develop guardrails, content filters, and output validation mechanisms
- Integrate AI security checks into CI/CD pipelines
- Ensure AI systems comply with GDPR and financial industry regulatory requirements
- Contribute to AI security standards and internal policies
Requirements
- 3 5+ years in software engineering, ML engineering, or application security
- Hands on experience with AI/ML systems — LLMs, NLP models, or similar
- Python proficiency for automation and scripting
- Experience working with Claude Code
- Strong understanding of cloud platforms: AWS, Azure, or GCP
- Experience with API security, Docker, Kubernetes
- Knowledge of AI specific security risks and mitigations
- Experience conducting threat modeling and risk assessments
Full Job Posting
Job Description
- We are looking for an AI Security Engineer to secure our AI driven systems, including LLM based applications, machine learning models, and AI enabled automation tools.
- This role will focus on identifying, assessing, and mitigating security risks across the AI lifecycle — from model development and training to deployment and runtime monitoring.
- The ideal candidate combines strong security engineering experience with a deep understanding of machine learning systems and emerging AI specific threats.
Key Responsibilities
- Design and implement security controls for AI/ML systems across development, training, and production
- Secure LLM integrations, RAG pipelines, and AI APIs
- Conduct threat modeling for AI systems and data pipelines
- Define secure by design patterns for AI powered features
- Identify and mitigate AI specific threats: prompt injection, jailbreak, model poisoning, adversarial attacks, data leakage, insecure serialization, excessive permissions
- Develop guardrails, content filters, and output validation mechanisms
- Implement monitoring for anomalous AI behavior
- Integrate AI security checks into CI/CD pipelines
- Perform security reviews of ML code and AI related infrastructure
- Secure model registries and artifact storage
- Ensure AI systems comply with GDPR and financial industry regulatory requirements
- Contribute to AI security standards and internal policies
Required Qualifications
- 3 5+ years in software engineering, ML engineering, or application security
- Hands on experience with AI/ML systems — LLMs, NLP models, or similar
- Python proficiency for automation and scripting
- Experience working with Claude Code
- Strong understanding of cloud platforms: AWS, Azure, or GCP
- Experience with API security, Docker, Kubernetes
- Knowledge of AI specific security risks and mitigations
- Experience conducting threat modeling and risk assessments
Preferred Qualifications
- Familiarity with RAG architectures, vector databases, ML pipelines (MLflow, Kubeflow, SageMaker)
- Experience in fintech or regulated environments
- Knowledge of AI governance frameworks (EU AI Act, NIST AI RMF, ISO/IEC 42001)
- Experience with AI red teaming
- Background in cybersecurity or application security (OWASP, Secure SDLC)
Soft Skills
- Strong analytical and problem solving skills
- Ability to translate technical risk into business impact
- Able to explain AI security risks and mitigations to non security teams
- Cross functional collaboration with ML, data, and product teams
- Clear documentation and communication skills
What you will get in return
- Competitive Salary
- Work Life Harmony
- Generous Time Off
- Employee Referral Program
- Comprehensive Health & Pension Benefits
- Workation Wonderland: 30 extra days to work remotely from anywhere
- Volunteer Days: two additional paid days each year
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