Description

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.

About the team
Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.