Sr. Consultant, Info Security, App, Data, Cloud Security - AI

Job Purpose and Impact

• TheSenior AI Security Engineerwill helpestablishand strengthen the security foundation for theCargill?smodern business applicationsby securing andoperatinga scalable, enterprise AI Platform. In this role, you will apply deepexpertiseincybersecurity, cloud platforms, and AI engineeringto protect AI capabilities used by data and application teams to deliver measurable business value.

  You will play a key role in enabling safe adoption ofGenerative AI, Large Language Models (LLMs), and Agentic AI systems, while ensuring security, resilience, and compliance are built in by design. The role also includescoaching and mentoring junior engineers,drivingautomationfirstsecurity practices, and delivering highly scalable AI security solutions across the enterprise

Key Accountabilities

• • Develop andmaintainsecurity and resilience forenterprisegradeAI and Generative AI services, supportingbusinesscriticaluse cases at scale.
  • Secure Large Language Models (LLMs), Agentic AI systems, and multiagent workflows, including inference services, finetuning pipelines, and runtime execution environments.
  • Implement security controls for Model Context Protocol (MCP) and similar agent integration patterns, protecting tool invocation, context exchange,agenttoagentcommunication, and external data access.
  • Develop and manage AI platform security capabilities across public cloud AI services,selfhostedmodels, andthirdpartyAI providers.
  • Build automated security guardrails using Python andpolicyascodeto enforce access control, data protection, model usage limits, and runtime monitoring.
  • Partner closely with AI Platform, Cloud Platform, DevOps, Software Engineering, and Compliance teams to embed security into the AI development lifecycle (AISDLC).
  • Perform threat modeling and risk assessments for AI architectures, including RAG pipelines, vector databases, agent frameworks, and model supply chains.
  • SupportAIrelatedincident response, including investigation, containment, remediation, and lessons learned for security incidents involving AI systems or agents.
  • Contribute to enterprise AI security standards, reference architectures, and best practices.
  • Act as a senior technical voice, mentoring junior engineers and influencing stakeholders across engineering and leadership teams

Qualifications

• • Bachelor?s orMaster?s degree in Computer Science, Cybersecurity, Artificial Intelligence / Machine Learning, ora relatedfield.
  • 6+ years of experience in cybersecurity engineering, withdemonstratedownership of complex, enterprise-scale systems.
  • Proven experience addressing the unique security challenges of Large Language Models (LLMs), Generative AI, or Agentic AI systems, including model misuse, prompt injection, hallucination risk, and data governance.
  • Strong understanding of cloud security concepts across AWS, Azure, and/or Google Cloud Platform, including IAM, networking, encryption, logging, and monitoring.
  • Hands-on experience with Python and security automation for scalable enforcement of AI security controls.
  • Experience securing containerized and distributed systems, including Kubernetes and service meshes.
  • Familiarity with AI platform components such as model registries, vector databases, RAG pipelines, fine-tuning workflows, and inference gateways

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