Senior AI Security Engineer

Deine Rolle im Team

Unsere Erwartungen an dich

Qualifikationen

• Practical knowledge of LLM-specific risks, such as:prompt injection and jailbreaks, data leakage and sensitive information exposure, model inversion, membership inference, supply chain risks in AI tooling and models.
• Solid understanding of the ML lifecycle and typical MLOps setups (data pipelines, training, evaluation, deployment, CI/CD, monitoring) and where to place security controls.
• Ability to read Python code and basic ML pipelines and to build small scripts/tools (e.g. for automated tests, log analysis, or prototype guardrails).
• Background in risk assessment and in writing or reviewing policy and governance documentation.
• Familiarity with relevant AI standards and frameworks, such as: ISO 42001, OWASP LLM Top 10, NIST AI RMF, OECD AI Principles.
• Understanding of EU AI Act obligations and how they apply to a fintech / financial services context, with the ability to map them to concrete controls.
• Strong grasp of data protection and privacy-by-design in AI (data minimisation, pseudonymisation/anonymisation, retention and deletion of training and log data).
• Background in financial services or fintech, or another highly regulated industry.
• Ability to translate technical AI risk into clear business language - you're comfortable presenting to both engineers and senior leadership.
• Comfort with ambiguity - AI regulation, standards and best practices are evolving quickly, and you help us navigate that.
• Collaborative, enabling mindset - you work through influence, coaching and partnership, not gatekeeping.
• You help teams ship valuable AI solutions safely, not stop them.

Erfahrung

• Demonstrable experience in Artificial Intelligence/Machine Learning security in a production context - not just general cybersecurity.
• Experience designing or reviewing secure architectures for AI/LLM systems, including: API security and authentication/authorization, secrets management (API keys, tokens, credentials), isolation of tenants/contexts and access control for data sources & vector stores, protection of sensitive data in prompts, logs and training data.
• Experience working side-by-side with data scientists or ML engineers - you have credibility in technical rooms and can challenge design decisions constructively.
• Experience reviewing AI vendor contracts or working with procurement/legal on technology and SaaS agreements.
• Prior audit or regulatory experience, ideally representing technical systems to auditors or financial regulators.
• Experience with logging, monitoring and incident response for AI or other high-risk systems.

Unser Angebot