AI Security Engineer

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At Crowe, your journey begins with a meaningful, rewarding career built on flexibility and impact. We embrace who you are, care for your well‑being, and nurture your growth across an 80‑year history of delivering service through innovation. To advance our services, we invest in AI‑enabled insights and technology‑powered solutions. Join us and help shape the future of our industry.

Everything we do is about making the future of human work more purposeful. We leverage state‑of‑the‑art technologies, modern architecture, and industry experts to create AI‑powered solutions that transform how our clients do business.

The new AI Transformation team will build on Crowe’s established AI foundation, furthering the capabilities of our Applied AI / Machine Learning team. By combining Generative AI, Machine Learning and Software Engineering, this team empowers clients to transform their business models through AI, irrespective of their current AI adoption stage.

• We invest in expertise. You’ll have the time, space and support to go deep in your projects and build lasting technical and strategic mastery. You’ll work with developers, product stakeholders, and project managers as a trusted leader and domain expert.
• We believe in continuous growth. Our team is committed to professional development and knowledge‑sharing.
• We protect balance. Our distributed team culture is grounded in trust and flexibility. We offer unlimited PTO, a flexible remote work policy, and a supportive environment that prioritizes sustainable, long‑term performance.

The AI Security Engineer I (Senior Staff) serves as a senior technical expert responsible for securing enterprise AI and machine learning systems across their full lifecycle, including data ingestion, model training, inference pipelines, retrieval‑augmented generation (RAG) systems, and generative AI applications. This role leads advanced security assessments, identifies vulnerabilities unique to AI‑enabled platforms, and architects secure‑by‑design solutions for cloud and hybrid environments.

Working closely with cybersecurity, cloud engineering, MLOps, data engineering, and AI engineering teams, the engineer designs and implements security controls that protect sensitive data, model artifacts, embeddings, and inference services from emerging threats. As a senior staff‑level contributor, this role influences architectural security decisions, advances AI‑specific threat detection and mitigation strategies, mentors engineers, and strengthens the organization’s overall AI security and responsible AI posture.

• Architecting secure deployment and operating models for AI, ML, and generative AI systems across cloud and hybrid environments.
• Conducting advanced AI security testing, including adversarial ML attacks, prompt injection simulations, and RAG manipulation assessments.
• Identifying and mitigating vulnerabilities in model‑serving infrastructure, feature stores, embedding pipelines, and vector databases.
• Designing guardrails, safety filters, access controls, and secure interaction patterns for LLM‑ and RAG‑based applications.
• Developing automated tooling to detect misconfigurations, insecure endpoints, and data exposure risks within AI pipelines.
• Collaborating with cloud and Dev Ops teams to secure Kubernetes clusters, GPU workloads, and infrastructure‑as‑code deployments.
• Analyzing logs, telemetry, and model outputs to detect anomalies, abuse patterns, model degradation, or malicious activity.
• Implementing encryption, secrets management, IAM policies, and network segmentation for AI workloads.
• Leading secure design and architecture reviews for AI features, APIs, and platform components.
• Documenting threat models, attack surfaces, risk assessments, mitigations, and compliance artifacts.
• Participating in AI‑specific incident response, investigation, and post‑incident analysis.
• Evaluating emerging AI security technologies, including model fingerprinting, inference protection, and secure execution environments.
• Supporting enterprise…