Principal Application Security Engineer - AI & Agentic Systems

Position Summary

Development, Standards & Secure Design

• Lead development and enforcement of application and AI security policies, standards, and guardrails, embedding security-by-design across both traditional and AI-driven systems.

• Establish secure design patterns for AI agent frameworks, covering prompt management, tool invocation, memory handling, autonomy boundaries, and escalation controls.

• Promote organization-wide awareness of AI-specific risks such as model misuse, prompt injection, data leakage, and unsafe agent behavior.

• Serve as the principal SME for securing AI-enabled applications and agentic system architectures.

• Architect and review secure designs for systems leveraging LLMs/foundation models, autonomous and semi-autonomous agents, RAG pipelines, and tool‑using or decision‑making workflows.

• Define identity, authorization, data access, and observability controls specific to agentic environments while partnering closely with AI platform, product, and data teams to ensure responsible AI delivery.

• Influence engineering and product teams to integrate secure engineering practices and align security with compliance, privacy, and responsible AI initiatives.

• Advise senior leadership on AI security implications, architectural decisions, and long-term strategy while shaping roadmaps that anticipate emerging AI threats and regulatory requirements.

• Lead advanced security testing and risk assessments for AI-enabled systems, including threat modeling of agent workflows, abuse/misuse analysis, and secure design reviews of AI pipelines.

• Evaluate and guide adoption of new AI security tools, ensuring protections maintain confidentiality, integrity, availability, and responsible data use.

• Provide senior technical leadership during incidents involving application or AI systems, guiding response strategies for misuse, data exposure, and autonomous failures.

• Translate operational learnings into improved security architecture, controls, and system resilience.

• Mentor senior and principal engineers to elevate security maturity across the organization.

• Contribute to research and evaluation of emerging AI security practices and play a key role in shaping the long-term application and AI security roadmap, advocating for security as a strategic accelerator for AI adoption.

• 10+ years of experience designing, building, and securing large-scale applications and platforms.

• 7+ years of expertise in application security, including threat modeling, secure design, and vulnerability management.

• 7+ years of programming experience in one or more languages such as Python, Java, JavaScript, C#, or Go.

• 5+ years of experience of developing and securing AI and ML workloads, with recent experience in generative AI and agentic workloads.

• 5+ years of experience public cloud platforms (AWS, Azure, and/or GCP) and modern application architectures.

• 3+ years of experience with containerized, serverless, and microservice-based architectures.

• Hands-on experience securing AI agents, RAG pipelines, and tool-using LLM systems.

• Proven ability to lead complex security initiatives from concept through enterprise-scale adoption.

• Familiarity with AI governance, responsible AI principles, and emerging AI security standards.

• Experience integrating security controls into CI/CD pipelines for AI and application workloads.

• Strong understanding of compliance frameworks (PCI, HIPAA, NIST, HITRUST, CSA).

• Experience influencing security strategy beyond a single team, including enterprise or platform-level impact.

• Contributions to security research, open-source projects, or industry communities.

• Bachelor’s degree or equivalent experience (High School Diploma and 4 years relevant experience)

The typical pay range for this role is:

$ - $

This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a…