AI Security Engineer

Job Summary

As AI Security Platform Lead, you will need strong understanding and proficiency with generative AI concepts, technologies and use-patterns. You will need to have strong interpersonal communication skills as this role owns the AI Security Platform(s) and must work with others to ensure continuous reliable, resilient and sustainable operation of the platform(s). You will work directly with cloud infrastructure teams, app developers, end users, operational support teams, security operations, vendors, and executive leadership stakeholders to maintain existing AI security capabilities and implement new improvements critical to AI-use policy enforcement and AI governance data collection. You will continuously assess performance and coverage of the AI Security Platform(s) to produce gap analyses, overall effectiveness reports, and new ideas for improvement.

Responsibilities

• 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.

Qualifications

• 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

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.