AI Security Engineer (m/f/n)

InPost is one of Europe’s leading out-of-home (OOH) e-commerce enablement platforms, providing delivery services via a network of over 64,000 Automated Parcel Machines and more than 30,000 pick-up and drop-off points across nine European countries. The company supports rapidly growing parcel volumes, delivering 1.4 billion parcels in 2025, and offers locker solutions that are cheaper, flexible, environmentally friendly, and contactless.

• 5+ years of experience in application security or product security.
• 5+ years of coding experience in one or more general-purpose languages, including shipping and operating production services.
• 5+ years of experience with security assessments, secure design reviews, or threat modelling.
• Solid understanding of generative AI, LLMs, and AI agents and their production deployment.
• Deep knowledge of AI-specific attack classes and their application in real systems.
• Experience securing agentic, code-execution, or LLM-integrated systems.
• Proven track record of finding and reasoning about real system vulnerabilities.
• Experience building engineered security controls.
• Hands-on cloud and container security experience with AWS, Azure, or GCP.
• Strong presentation skills with the ability to communicate complex security topics clearly.
• Good English communication skills.

Nice to have:

• Experience building security automation or developer-facing security tooling.
• Working knowledge of the OWASP Top 10 for LLM Applications and OWASP Top 10 for Agentic Applications.
• Working knowledge of MITRE ATLAS.

• Work on the security assessment and secure design review of AI, LLM, and agentic systems across InPost's technology estate.
• Identify, reproduce, and reason about real vulnerabilities in AI-powered and agentic systems, collaborating with engineering teams to fix root causes.
• Define and build engineered security controls for AI/ML and LLM-related risks.
• Build security automation and developer-facing tooling to help product and engineering teams build securely by default.
• Review new AI solutions and system architectures for security risk.
• Represent security in AI governance forums and the AI solutions catalogue.
• Apply hands-on cloud and container security practices across AWS, Azure, and GCP to secure AI system infrastructure.
• Serve as a subject matter expert on AI-specific attack classes.
• Translate complex technical and security findings into clear, practical guidance for business stakeholders.