AI-Application Security Architect

Stifel•Saint Louis, MO

About The Position

The AI-Application Security Architect is responsible for defining, governing, and advancing the enterprise AI / application security architecture across the organization. This role provides strategic and technical leadership to ensure applications are designed and built securely at scale, aligned with business objectives, regulatory requirements, and evolving threat landscapes. Acting as a trusted advisor to engineering leadership, this role balances risk reduction with development velocity and innovation.

Requirements

Deep understanding of security principles, methods and technologies related to application development, deployment, and maintenance.
Experience with industry standard security frameworks, such as OWASP, SANS, or NIST.
Knowledge of various programming languages, such as Java, .NET, and Python.
Experience with security testing tools, such as Nessus, Metasploit, and Burp Suite.
Strong analytical and problem-solving skills, with the ability to identify and mitigate security risks.
Strong understanding of cloud computing and associated security risks.
Excellent communication skills, with the ability to effectively communicate complex security issues to technical and non-technical audiences.
Bachelor's degree in Computer Science, Information Security, or a related field, or equivalent experience.
7+ years of experience in application security architecture, design, and development.
Expertise in code analysis and testing tools.
Expertise in web application firewalls.
Ability to understand and support multiple programming languages and frameworks.
Understanding of encryption and key management solutions.
Experience with working with multiple authentication methods and protocols.
Experience with office productivity, reporting, and technical documentation software.

Nice To Haves

Master's degree in Computer Science, Information Security, or a related field.
Professional security certifications, such as CISSP, CISM, or SANS GIAC.

Responsibilities

Design and lead the implementation of enterprise-wide AI / application security strategies, policies, standards, and reference architectures aligned with business objectives, regulatory requirements, and industry best practices.
Partner closely with software engineering, platform, and DevOps teams to embed security throughout the SDLC, promoting a secure-by-design culture and enabling scalable, automated security controls.
Lead and oversee AI / application architecture reviews, threat modeling exercises, and design risk assessments to proactively identify and mitigate security risks.
Define, validate, and prototype security architecture patterns through hands-on evaluations, proof-of-concepts (POCs), and technical deep dives, ensuring proposed controls are practical and effective.
Establish and maintain secure design patterns and reference architectures for modern application stacks, including AI, cloud-native, microservices, APIs, and event-driven systems.
Define and govern the integration application security tooling (SAST, DAST, SCA, secrets scanning, CI/CD controls) to improve coverage, consistency, and developer adoption.
Develop and maintain AI / application security metrics and KPIs to measure program maturity, communicate risk posture to leadership, and drive continuous improvement.
Serve as a subject matter expert (SME) and escalation point for complex AI / application security design decisions, risk exceptions, and non-standard architectures.
Establish and enforce AI / application security architecture governance, including design review checkpoints, standards enforcement, and defined escalation paths for non-compliant designs.
Collaborate with enterprise architecture, cloud security, infrastructure, and GRC teams to ensure application security controls are aligned across platforms and technologies.
Research and evaluate emerging threats, security technologies, frameworks, and industry trends, recommending strategic improvements to the enterprise application security architecture.
Mentor and provide technical guidance to AI / application security engineers and development teams, raising overall security maturity and architectural consistency.
Lead AI-specific application threat modeling, addressing risks such as prompt injection, model inversion, data poisoning, unauthorized model access, and misuse of generative outputs.
Define and govern secure architecture patterns for AI-enabled applications, including controls for data protection, identity, authorization, logging, and monitoring.
Establish security and governance standards for the adoption of third-party AI platforms and APIs, ensuring alignment with enterprise security, privacy, and risk management frameworks.
Partner with legal, compliance, and risk teams to ensure responsible and compliant use of AI capabilities, consistent with enterprise risk tolerance and regulatory expectations.