AI Security Engineer

The AI Security Platform Lead acts as a vital member of Syngenta’s Information Security team to help safeguard Syngenta Information Technology infrastructure against AI-related cyber threats and vulnerabilities.

The AI Security Platform Lead bridges end users, developers, operational run/support teams and other functional stakeholders to maintain reliable operation of AI Security Platform(s) while driving continuous and sustainable improvement and providing regular transparent performance & security metric reporting Accountabilities: Cross-Platform AI Policy Enforcement: Manage and optimize security controls across endpoints, SaaS environments, and run-time interactions to monitor AI agent behaviors and protect against data exfiltration.

AI Asset Discovery & Posture Management :Leverage the AI Security Platform to maintain a comprehensive inventory of private and public AI tools while ensuring continuous visibility and security posture across AWS, Azure, GCP.

AI Red Teaming : Work with Syngenta application development teams to maintain CI/CD integration of automated AI security Red-Teaming tests that assess internally developed AI agents for security and AI use-policy compliance.

Vendor Management & Roadmap : Act as the primary technical point of contact for the AI Security Platform vendor, influencing their product roadmap to meet Syngenta’s evolving AI security needs and staying ahead of new feature releases.

Scalability & Performance Tuning : Ensure the AI Security Platform(s) AI security architecture scales effectively with enterprise growth, minimizing latency for end-users while maintaining rigorous inspection standards.

Incident Response Integration : Partner with the SOC (Security Operations Center) to develop playbooks for responding to AI-specific threats detected by the AI Security Platform(s).

Collaboration and Communication: Collaborate closely across functional, regional and business unit teams and stakeholders to proactively identify, recommend and develop continuous improvements for AI cybersecurity tooling, event detection, correlation and incident response.

Documentation and Knowledge Management: Maintain comprehensive documentation of the AI Security Platform, operational procedures, contacts, and security findings for knowledge sharing and audit purposes.

Experience managing a large-scale enterprise security solution including capability road-mapping and operational change management Strong understanding of generative AI concepts such as LLMs, RAG, MCP servers, AI agent frameworks, agent loops, agent Red-Teaming, model routing, model gateways, guardrails technologies, LLM context windows, private AI vs public AI and more Familiarity with EU AI Act, OWASP LLM Top 10 and other emerging AI regulatory and security frameworks Hands-on experience with cloud-native security tools and API-based integrations with cloud, network, security SIEM, firewalls, intrusion detection systems, endpoint security, application development IDEs and agentic coding tools Experience with Data Loss Prevention (DLP) specifically tailored for LLMs and generative AI prompts.

Excellent analytical, problem-solving, and troubleshooting skills Strong communication and interpersonal skills Ability to work independently and as part of a team