Do you want to set the standard for how builders architect AI workloads that are secure, reliable, and efficient on AWS - with security as the foundation? We are looking for a Principal Security Solutions Architect with deep expertise in Machine Learning, Generative AI, and Agentic AI to own and drive the strategic vision for Security-focused Architectural Guidance Best Practices across AI workloads. You will operate at the intersection of AI technologies, cloud architecture, and security engineering, ensuring AI workloads achieve Well-Architected outcomes across all six pillars - Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability - with depth in the Security pillar. You will influence both internal AWS teams and the broader builder community.

In this role, you will define the long-term technical direction for AI security architectural guidance, translate emerging AI/ML security patterns into prescriptive and actionable best practices grounded in the Well-Architected pillars, and influence AWS service design to better serve AI builders who need to secure their workloads across the full AI lifecycle.

Key job responsibilities

- Set Strategic Technical Direction for AI Security: Define and own the long-term vision and roadmap for AI/ML security architectural guidance aligned to the AWS Well-Architected Guidance pillars, with deep focus on the Security pillar - including identity, access control, data protection, data residency and sovereignty, threat detection, and incident response for AI workloads.

- AI Security & Generative AI Thought Leadership: Serve as the organization's principal technical authority on securing AI architectures - covering model security, data pipeline protection, prompt injection mitigation, model poisoning prevention, inference endpoint hardening, and secure agentic workflows. Provide guidance on security considerations for foundation models, RAG pipelines, fine-tuning, multi-agent orchestration, and responsible AI practices. Drive consensus on complex, ambiguous security decisions in AI systems.

- Raise the Bar Across the Organization: Establish security standards, review mechanisms, and architectural guardrails that elevate the entire guidance portfolio. Define what "great" looks like for AI security guidance and hold the team accountable.

- Influence Service Roadmaps: Partner with Stakeholders and Engineers across AWS service teams (Amazon Bedrock, SageMaker, Q, AWS Security services, etc.) to represent the customer voice on AI security, validate architectural recommendations, and influence product direction based on security patterns observed in production AI workloads.

- Executive Customer Engagement: Engage directly with strategic enterprise customers to validate security guidance through real-world implementations, identify emerging AI security challenges, and translate insights into scalable best practices.

- Drive Innovation in Content Delivery: Own the strategy for automation tooling and pipelines (including Generative AI-assisted authoring) that accelerate the creation, review, and publication of AI security guidance at scale. Define mechanisms that ensure guidance remains current as the AI threat landscape evolves rapidly.

- External Thought Leadership: Publish whitepapers, blog posts, and reference architectures; present at AWS events (re:Invent, Summits, webinars) and industry security conferences to establish AWS as a leading authority on securing Well-Architected AI workloads.

- Mentorship & Organizational Impact: Mentor senior architects on AI security best practices, drive hiring bar-raising, and build a community of practice that scales AI security architectural expertise across the organization. Contribute to organizational strategy and workforce planning.

- Mechanisms & Operational Excellence: Design and implement repeatable mechanisms (e.g., security review processes, threat modeling for AI workloads, guidance lifecycle management, feedback loops) that ensure sustained quality and relevance at scale.

- Hands-On Technical Validation: Validate security architectural recommendations through prototyping, proof-of-concept implementations, threat modeling exercises, and code samples that demonstrate secure AI patterns.

BASIC QUALIFICATIONS

- Bachelor's degree or above in Computer Science, Computer Engineering, Cybersecurity, or other related discipline

- 10+ years of experience in solutions architecture, security architecture, or a senior technical role with increasing scope and impact

- 7+ years of hands-on experience in cloud security, application security, or infrastructure security

- Deep understanding of the end-to-end ML lifecycle from a security perspective: secure data preparation, model integrity, supply chain security, deployment hardening, monitoring, and governance

- Demonstrated expertise in security domains: identity and access management, encryption, network security, threat modeling, vulnerability management, and compliance

- Demonstrated ability to influence technical direction across organizational boundaries without direct authority

- Experience with AWS security and AI/ML services (IAM, KMS, GuardDuty, Security Hub, Bedrock, SageMaker, etc.)

- Exceptional written and verbal communication skills with a track record of publishing authoritative technical content (whitepapers, guidance documents, reference architectures) for executive and technical audiences

- Proven ability to work with cross-functional senior leadership to define and implement security architectural standards at organizational scale.

PREFERRED QUALIFICATIONS

- Deep expertise in securing Generative AI architectures: model access controls, data leakage prevention, prompt injection defenses, RAG pipeline security, vector database access patterns, and secure fine-tuning workflows

- Hands-on experience securing Agentic AI patterns: permission boundaries for autonomous agents, secure tool-use architectures, least-privilege orchestration, audit trails, and human-in-the-loop approval gates

- Expert-level knowledge of AWS security and AI/ML services: AWS IAM, KMS, CloudTrail, GuardDuty, Security Hub, Macie, Amazon Bedrock Guardrails, Amazon SageMaker (with VPC, encryption, role-based access), and related services

- Experience defining or contributing to the AWS Well-Architected Guidance (Security pillar) or similar enterprise-scale security review guidance

- Recognized thought leader with a strong publication record and conference speaking history (re:Invent, AWS Summits, industry security/architecture conferences, or equivalent)

- Experience with Infrastructure as Code (CDK, CloudFormation, Terraform) and CI/CD practices for secure ML pipelines (MLSecOps)

- Deep knowledge of responsible AI practices: fairness, explainability, safety guardrails, governance standards, and regulatory compliance (SOC 2, ISO 27001, NIST AI RMF, EU AI Act)

- AWS certifications (Solutions Architect Professional, Security Specialty, Generative AI, or equivalent)

- Demonstrated experience mentoring senior engineers on security practices and contributing to organizational hiring and talent development strategy

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CA, Irvine - 182,800.00 - 247,300.00 USD annually

USA, TX, Dallas - 182,800.00 - 247,300.00 USD annually

USA, WA, Bellevue - 182,800.00 - 247,300.00 USD annually