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 (prompt injection, model poisoning, data leakage, adversarial attacks).
Key Responsibilities
- AI/ML Security Architecture
- 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
- AI Threat Detection & Mitigation
- Identify and mitigate AI-specific threats: prompt injection, jailbreak techniques, model poisoning, data contamination, adversarial attacks, training data leakage, insecure model serialization, excessive permissions in AI agents
- Develop guardrails, content filters, and output validation mechanisms
- Implement monitoring for anomalous AI behavior
- Secure Development & DevSecOps
- Integrate AI security checks into CI/CD pipelines
- Perform security reviews of ML code and AI-related infrastructure
- Secure model registries and artifact storage
- Collaborate with other engineers and platform teams to enforce security standards
- Data Protection & Compliance
- Ensure AI systems comply with GDPR, data privacy regulations, financial industry regulatory requirements
- Implement controls for sensitive data used in training and inference
- Perform AI risk assessments aligned with internal risk methodology
- Governance & Policy
- Contribute to AI security standards and internal policies
- Define AI risk classification and control frameworks
- Support security reviews for new AI initiatives and tools
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
Benefits
- Competitive Salary – We believe great work deserves great pay; your skills and talents will be rewarded with a salary that makes you feel valued and motivated
- Work‑Life Harmony – Join a company that genuinely cares about you – because your life outside of work matters just as much as your time on the clock
- Generous Time Off – Our annual leave policy lets you recharge and enjoy life outside of work without a worry
- Employee Referral Program – Love working here? Bring your talented friends on board and get rewarded for growing our awesome team
- Comprehensive Health & Pension Benefits – From medical insurance to pension plans, we’ve got your back. Plus, location‑specific benefits and perks!
- Workation Wonderland – Live your digital nomad dreams with 30 extra days to work remotely from anywhere in the world (some restrictions apply). Adventure awaits!
- Volunteer Days – Make a difference! Take two additional paid days each year to support causes you care about and give back to the community