AI Security Engineer

Description

Summary: As an AI Security Engineer, you'll secure AI use cases, agents, and platforms by design, aligning with group-wide security frameworks and policies. Highlights: 1. Embed security by design across AI use cases, agents, and platform integrations 2. Address AI-specific risks like prompt injection and data leakage 3. Strengthen AI incident readiness and scale secure AI delivery Hey there, think you stumbled upon this job posting by chance? We dont believe in chance at Nimber. Caught your eye? Great. Keep going... We are Nimber, and we are not just filling positions, we are building a team that is ready to shake things up. If you are ready to rewrite the rules and make a real impact, this is your moment. Join us and lets put the future where it belongs. In the hands of passionate people. But what does Nimber mean?In mathematics and game theory, they are numbers with special properties of addition and multiplication. And what we really want is to add value to customers' projects. **Position:** AI Security Engineer **Location:** Hybrid **Job Summary**: As AI Security Engineer, you are the first line security engineering role within the Central AI team / AI Hubs. Your mission is to ensure that AI use cases, agents, and supporting platform components are built and operated securely by design and in line with the groupwide security framework. **Key Responsibilities:** * Embed security by design across AI use cases, agents, and platform integrations, with strong controls for access, secrets, logging, monitoring, sandboxing, tool and API restrictions, and external integrations; * Translate group security policies and architecture into practical controls, reusable patterns, and guidance for AI teams, ensuring alignment with risk, third\-party, supplier, and operational requirements; * Prepare security\-gate evidence, drive remediation from reviews, and escalate unresolved control gaps, deviations, or delivery risks; * Address AI\-specific risks such as prompt injection, data leakage, insecure tool use, excessive permissions, and weak auditability through hardening and secure deployment patterns; * Support due diligence and secure implementation for external AI vendors, models, orchestration components, and APIs, with the right safeguards for data protection and segregation; * Strengthen AI incident readiness through detection, logging, response scenarios, playbooks, exercises, and close collaboration with SOC and central security teams; * Scale secure AI delivery through reusable patterns, stronger hub capability, and lessons shared back into the groupwide security model. **Requirements:** * 7\+ years in IT and cyber security, with at least some of that in transformation, digital or platform contexts; * Solid technical grounding in cloud security, identity and access management, application security and secure SDLC; * Working knowledge of AI/ML and Agentic AI security: prompt injection, data leakage, agent identity, tool\-use risk, model supply chain. Familiarity with OWASP LLM Top 10, MITRE ATLAS and NIST AI RMF; * Experienced with threat modeling, risk assessment and security architecture for distributed systems; * Strong stakeholder management; able to challenge solution designs constructively and influence without full hierarchical authority; * Pragmatic, outcome\-driven, biased for delivery; resilient under ambiguity; * Fluent English; an additional European language is a plus. This is our winning strategy, built on the core principles of impartiality, independence, and fairness at Nimber. The only thing missing is you! Ready to join us and succeed? If you're tired of feeling like just a number, send us your application and become a Nimber.