Job 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 Senior 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 of 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. - 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. A day in the life You start your morning reviewing a customer's architecture proposal, identifying areas where you can simplify complexity and reduce operational overhead. By midday, you are leading a technical deep-dive with a customer's engineering team, walking through design choices and trade-offs. Later, you collaborate with internal partners to unblock a delivery milestone, then wrap up by contributing a reusable reference design that other architects can leverage. 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. - Bachelor's degree in computer science, engineering, mathematics or equivalent - 7+ years of experience in solutions architecture, security architecture, or a senior technical role with increasing scope and impact - 3+ 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.) - Knowledge of AWS services, market segments, customer base and industry verticals - 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 Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit amazon.jobs for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. 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 amazon.jobs . USA, CA, Irvine - 153,600.00 - 207,800.00 USD annually USA, TX, Dallas - 153,600.00 - 207,800.00 USD annually USA, WA, Bellevue - 153,600.00 - 207,800.00 USD annually

Requirements

Must-haves

Key job responsibilities
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.
A day in the life
About the team
Diverse Experiences
Inclusive Team Culture
Work/Life Balance
Bachelor's degree in computer science, engineering, mathematics or equivalent
7+ years of experience in solutions architecture, security architecture, or a senior technical role with increasing scope and impact
3+ 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.)
Knowledge of AWS services, market segments, customer base and industry verticals
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
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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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Keywords to mirror

aiawsmachine learningmlci/cd

Platform: amazon
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave