Senior AI Application Security Engineer

PepsiCo•Plano, TX

1d•$93,500 - $156,450

About The Position

PepsiCo’s Global Application Security Program integrates security into software development at enterprise scale. As AI becomes a core component of enterprise applications, our mission expands to ensure AI systems are designed, developed, deployed, and operated securely by default. This role serves as a senior technical contributor responsible for designing, implementing, and advancing AI Application Security capabilities. The ideal candidate brings deep technical expertise across AI systems, application security, and cloud-native architectures to solve complex security challenges and enable secure AI adoption across the enterprise.

Requirements

Advanced knowledge of secure software development, secure architecture, and application security engineering.
Advanced experience performing application and AI threat modeling using frameworks such as STRIDE, PASTA, or equivalent.
Deep understanding of the OWASP Top 10, OWASP Top 10 for LLM Applications, and secure software engineering practices.
Strong experience designing and securing cloud-native applications in AWS (preferred), Azure, or GCP.
Strong proficiency in Python and/or Go.
Experience integrating security into CI/CD pipelines and DevSecOps workflows.
Deep understanding of modern AI architectures, including: Large Language Models (LLMs), AI Agents, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Embeddings and Vector Databases, Tool Calling and Function Execution, AI Memory and Context Management, Multi-Agent Systems.
Experience mitigating AI threats including prompt injection, model poisoning, jailbreaks, insecure tool execution, excessive agency, prompt leakage, sensitive data disclosure, and AI supply chain attacks.
Experience evaluating AI security technologies such as Promptfoo, NVIDIA Garak, Protect AI, Lakera, HiddenLayer, Microsoft AI Security, or equivalent.
Experience with AI development frameworks such as LangChain, LangGraph, Semantic Kernel, MCP, OpenAI SDK, Azure AI Foundry, Amazon Bedrock, or similar.
Strong understanding of identity, authorization, API security, cryptography, secrets management, and runtime security for AI systems.
Strong written, verbal, and presentation skills.
High integrity with sound judgment and accountability.
Exceptional analytical, troubleshooting, and systems-thinking abilities.
Self-motivated with a passion for solving complex technical problems.
Strong collaboration and communication skills across engineering teams.
Comfortable working in a fast-paced, global environment with evolving technologies and ambiguity.
Ability to perform effectively under pressure.

Responsibilities

Design and implement advanced security controls for AI-enabled applications, including LLMs, AI agents, RAG pipelines, MCP servers, and AI workflows.
Perform complex AI application threat modeling and security architecture assessments for high-risk systems.
Design and implement reusable AI security capabilities, libraries, frameworks, and automation to improve security at scale.
Develop security controls for prompts, agent memory, tool execution, model interactions, identity, authorization, and sensitive data protection.
Research, prototype, and evaluate emerging AI security technologies, attack techniques, and defensive capabilities.
Identify and mitigate AI-specific threats, including prompt injection, indirect prompt injection, model poisoning, jailbreaks, insecure tool execution, excessive agency, sensitive data disclosure, and AI supply chain risks.
Design and integrate AI security controls into enterprise AI platforms, CI/CD pipelines, and developer workflows.
Develop reusable reference implementations, security patterns, and engineering guidance for AI-enabled applications.
Partner with development, platform engineering, architecture, and Data & AI teams to solve complex AI security challenges.
Conduct advanced security assessments, code reviews, and architecture reviews for AI-enabled applications.
Evaluate AI security tooling and recommend improvements to increase detection accuracy, automation, and operational efficiency.
Develop technical documentation, implementation guides, and engineering standards for AI security capabilities.
Contribute to AI security metrics and continuously improve platform effectiveness and security posture.
Mentor junior engineers through technical coaching, design reviews, and knowledge sharing.
Support AI security investigations, incident response, and complex vulnerability remediation.
Participate in Agile planning and contribute to strategic Application Security initiatives.
Participate in a 24/7 on-call rotation, including weekends and holidays.