AI Security Engineer (m/f/n)

InPost is a leading out-of-home (OOH) e-commerce enablement platform in Europe, with a network of over 64,000 Automated Parcel Machines (APMs) and more than 30,000 pick-up and drop-off (PUDO) points across nine European countries. Founded in 1999, InPost supports rapidly growing parcel volumes with 1.4 billion parcels delivered in 2025, offering cheaper, flexible, environmentally friendly, and contactless delivery options.

• 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, including deployment in production.
• Deep knowledge of AI-specific attack classes and their implications for real systems.
• Experience securing agentic, code-execution, or LLM-integrated systems.
• Proven track record of finding and reasoning about real vulnerabilities.
• Experience building engineered security controls.
• Hands-on cloud and container security experience on AWS, Azure, or GCP.
• Strong presentation skills for communicating complex technical and security topics to diverse stakeholders.
• Good English skills for confident communication in an international environment.

Nice to have:

• Background building security automation or developer-facing security tooling.
• Working knowledge of the OWASP Top 10 for LLM Applications and 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 enable secure-by-default product and engineering practices.
• 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.
• Act as a go-to expert on AI-specific attack classes to keep defenses ahead of evolving threats.
• Translate complex technical and security findings into clear, practical guidance for business stakeholders.