Principal AI Security SA, AWS Security & Networking

Application deadline: Aug 26, 2026

Amazon Web Services (AWS) is seeking a Principal AI Security Solutions Architect to define and drive technical strategy for secure AI adoption and AI-enabled security outcomes across North America. You will work with CISOs, Chief AI Officers, security leaders, enterprise architects, and builders as they move generative AI and agentic systems into production.

Customers need security architectures that support the speed and autonomy of AI systems while preserving control over identities, data, permissions, software supply chains, and runtime actions. Security organizations are also evaluating how AI can improve detection, investigation, vulnerability prioritization, remediation, and analyst productivity. You will help customers make sound decisions across both areas, define measurable outcomes, and carry the lessons from individual engagements into guidance that serves the broader field.

You will operate across organizational boundaries and in areas where the business objective, technology strategy, and solution design remain ambiguous. You will align account teams, security and AI specialists, service teams, partners, and field communities around a coherent technical direction. Your work will produce reference architectures, decision frameworks, assessments, customer offerings, and operating mechanisms that other Solutions Architects can apply consistently.

This is a customer-facing Principal Solutions Architect role. Success requires the ability to move between executive strategy and deep architecture, influence product and field priorities with customer evidence, and build mechanisms that continue producing results without direct involvement from the role holder.

Key job responsibilities

• Own the multi-year technical strategy for Security AI across the AGS Security & Networking SA Team, including priorities, architectural positions, field mechanisms, success measures, and cross-organization dependencies.
• Advise senior customer leaders on security strategy for AI adoption, translating business goals and risk tolerance into clear architecture decisions, governance models, investment priorities, and measurable outcomes.
• Lead significantly complex customer engagements involving generative AI and agentic systems, including agent identity, least privilege, data protection, prompt and context risks, retrieval security, memory, tool and connector access, software supply chain risk, adversarial testing, runtime monitoring, incident response, and auditability.
• Define architectures for applying AI to security workflows such as detection, triage, investigation, vulnerability prioritization, security posture analysis, remediation, and control validation. Establish evaluation criteria for accuracy, safety, explainability, human oversight, and operational impact.
• Turn recurring customer problems into repeatable field mechanisms, including reference architectures, decision frameworks, assessments, workshops, reusable demonstrations, implementation guidance, engagement qualification, and escalation paths.
• Establish outcome measures that connect technical work to reduced risk, faster secure deployment, improved detection or response, customer adoption, field reuse, and product improvement. Use these measures to adjust strategy and resource focus.
• Build durable working relationships across AWS security and AI service teams, AGS field organizations, the Security and AI/ML Technical Field Communities, account teams, Professional Services, Support, and AWS Partners.
• Gather evidence across customers and use it to influence product strategy, roadmap priorities, service integration, documentation, and field investment. Represent customer requirements in product narratives and senior leadership reviews.
• Create executive and technical narratives that give customers and AWS teams a clear point of view on secure AI adoption and AI-enabled security. Represent AWS in customer forums and industry events where deep technical judgment is required.
• Develop Principal-level technical capability across the SA community through mentoring, architecture reviews, content standards, technical assessments, and communities of practice.
• Identify emerging security risks and capability gaps early, determine which require customer guidance, field education, partner engagement, or product investment, and lead the right organizations toward resolution.
• Serve as an escalation point for high-impact customer decisions where AI architecture, security risk, business priorities, and multiple AWS organizations intersect.

A day in the life

A day may begin with a CISO and Chief AI Officer working session on the control model for production agents that can access sensitive data and take actions through external tools. You may then review a proposed reference architecture with security and AI service teams, resolve conflicting design assumptions, and document the decision criteria for field use.

Later, you may examine results from customer engagements to identify a recurring gap in agent identity, AI workload detection, or AI-assisted investigation. You will decide whether the right response is a customer offering, a reusable architecture, a field enablement mechanism, a partner pattern, or product feedback. You may close the day mentoring a Principal candidate, reviewing an executive narrative, or presenting a data-backed investment recommendation to Directors and VPs.

About the team

The AGS Security & Networking SA Team is part of AWS Customer Solutions & Scale Innovation within AGS NAMER Tech. The team includes Solutions Architects across the United States and Canada who help customers connect and operate applications securely and resiliently on AWS.

Our mission is to accelerate customers" confidence in the cloud through secure and well-connected operations. We work directly with customers, account teams, service teams, and partners to solve complex security and networking problems, create reusable guidance, and turn field evidence into improvements across AWS. The team"s 2026 AI security goal covers both security for AI and AI for security, with an emphasis on opinionated guidance, direct customer work, and mechanisms that scale beyond one contributor.