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Brillio

Technology consulting for AI-driven digital transformation

Staff AI Security Engineer - AI

Security Engineering & ArchitectureConfirmed live in the last 24 hours
Full-timeSeattle, WA, USA$120k - $130k /yrIn-person

About the Job

Requirements

  • At least 7 years of experience in information security, cybersecurity, or security engineering, including at least 2 years focused on AI/ML security or Large Language Model application security.
  • Strong understanding of AI/ML technologies, including transformer architectures, Large Language Models, Retrieval-Augmented Generation, prompt engineering, agentic AI and autonomous AI workflows, and the OWASP Top 10 for LLM Applications.
  • Deep technical expertise in cloud security, particularly AWS and GCP, including identity and access management, containerization, Kubernetes, and DevSecOps methodologies.
  • Hands-on experience with AI/ML security architectures, production AI deployments, and securing the end-to-end AI development lifecycle.
  • Strong knowledge of AI-specific security threats, including prompt injection, jailbreak attacks, model poisoning, model manipulation, sensitive data exposure, and data extraction.
  • Experience implementing threat detection, security architecture controls, and automated security mechanisms for AI/ML environments.
  • Proficiency in Python or Go, with experience developing production-grade integrations, security automation tools, and security pipelines.
  • Experience assessing third-party AI platforms, foundation models, and AI technology supply chains.
  • Working knowledge of AI governance frameworks, emerging regulatory requirements, data privacy, and Responsible AI principles.
  • Strong analytical and problem-solving skills to identify and address security gaps across complex AI/ML workflows.
  • Excellent communication and stakeholder management skills to translate emerging AI security risks into actionable technical roadmaps and business impact for executive leadership.

Responsibilities

  • Define and drive the long-term AI and Agentic AI security roadmap, including security architecture, technical standards, and implementation strategies in collaboration with AI platform and engineering teams.
  • Design and implement technical security controls to protect AI environments, including autonomous agent permissions, blast radius management, and advanced prompt injection detection.
  • Establish centralized security standards for Model Context Protocol implementations and oversee secure, resilient Model Context Protocol hosting infrastructure supporting autonomous AI agents.
  • Conduct adversarial security assessments and AI red teaming exercises across machine learning systems to identify vulnerabilities related to model manipulation, data extraction, and unauthorized access.
  • Lead threat modeling initiatives and security architecture assessments for emerging AI capabilities, Retrieval-Augmented Generation pipelines, autonomous workflows, and AI-powered applications.
  • Evaluate the security posture, privacy controls, data handling practices, and retention policies of third-party foundation models, AI platforms, and vector databases.
  • Advise on AI tooling evaluations and data classification initiatives, and develop standardized security assessment frameworks to ensure consistent risk management and compliance.
  • Establish and scale AI security governance frameworks, technical policies, and organizational standards to promote secure and responsible AI engineering practices.
  • Develop and communicate practical AI security guidelines to help engineering teams, business stakeholders, and leadership safely adopt and leverage AI technologies.
  • Architect, deploy, and automate real-time security controls for Large Language Model inputs and outputs, including prompt injection prevention, jailbreak detection, and AI response validation.

Desired Qualifications

  • Hands-on experience with Model Context Protocol frameworks and autonomous multi-agent AI systems.
  • Strong understanding of AI-specific security and regulatory requirements, including data residency and data localization requirements; data loss prevention and content protection controls for AI-generated outputs; permission boundaries and access restrictions for autonomous AI agents; and external OAuth authorization and access-scoping mechanisms.
  • Experience developing and implementing enterprise AI governance frameworks and AI enablement programs.
  • Background in designing and implementing AI platform security architectures.
  • Experience establishing security standards and governance models for enterprise-wide AI adoption.

About the Company

Brillio

Technology consulting for AI-driven digital transformation

Brillio helps organizations move their systems and processes into the digital world by providing technology consulting and customized AI and cloud-based solutions. The company works with large clients, including many Fortune 500 firms, and has a strong emphasis on the healthcare sector. Its offerings include designing and building tailored software and workflows that improve efficiency, security, and scalability, and enabling real-time, AI-powered interactions through generative AI tools. Customers typically engage Brillio through long-term support contracts or project-based work, paying for both advisory services and the implementation of technology solutions. Brillio’s goal is to help clients become ‘generative enterprises’—organizations that leverage AI and cloud technologies to continuously transform operations and user experiences, stay competitive, and drive measurable business outcomes.

Company size
5,001-10,000
Company stage
Late Stage VC
Total funding
Not listed
Headquarters
Dallas, TX
Founded
2014

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