Do you want to set the standard for how builders architect AI workloads that are secure, reliable, and efficient on AWS? We are looking for a Principal Solutions Architect with deep expertise in Machine Learning, Generative AI, and Agentic AI to own and drive the strategic vision for Architectural Guidance Best Practices across AI workloads. You will operate at the intersection of AI technologies and cloud architecture, ensuring AI workloads achieve Well-Architected outcomes across all six pillars Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability influencing both internal AWS teams and the broader builder community. In this role, you will define the long-term technical direction for AI architectural guidance, translate emerging AI/ ML patterns into prescriptive and actionable best practices grounded in the Well-Architected pillars, and influence AWS service design to better serve AI builders worldwide. Key job responsibilities- Set Strategic Technical Direction: Define and own the long-term vision and roadmap for AI/ ML architectural guidance aligned to the AWS Well-Architected Guidance pillars.- Generative AI & Agentic AI Thought Leadership: Serve as the organization's principal technical authority on architectures involving foundation models, retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering, agentic workflows, multi-agent orchestration, and responsible AI practices. Drive consensus on complex, ambiguous technical decisions.- Raise the Bar Across the Organization: Establish quality standards, review mechanisms, and architectural guardrails that elevate the entire guidance portfolio. Define what "great" looks like and hold the team accountable.- Influence Service Roadmaps: Partner with Stakeholders and Engineers across AWS service teams (Amazon Bedrock, Sage. Maker, Q, etc.) to represent the customer voice, validate architectural recommendations, and influence product direction based on patterns observed in production AI workloads.- Executive Customer Engagement: Engage directly with strategic enterprise customers to validate guidance through real-world implementations, identify emerging architectural challenges, and translate insights into scalable best practices.- Drive Innovation in Content Delivery: Own the strategy for automation tooling and pipelines (including Generative A - Iassisted authoring) that accelerate the creation, review, and publication of guidance at scale. Define mechanisms that ensure guidance remains current as the AI landscape evolves rapidly.- External Thought Leadership: Publish whitepapers, blog posts, and reference architectures; present at AWS events (re:Invent, Summits, webinars) and industry conferences to establish AWS as the definitive authority on Well-Architected AI.- Mentorship & Organizational Impact: Mentor senior architects, drive hiring bar-raising, and build a community of practice that scales AI/ ML architectural expertise across the organization. Contribute to organizational strategy and workforce planning.- Mechanisms & Operational Excellence: Design and implement repeatable mechanisms (e.g., architectural review processes, guidance lifecycle management, feedback loops) that ensure sustained quality and relevance at scale.- Hands-On Technical Validation: Validate architectural recommendations through prototyping, proof-of-concept implementations, and code samples that demonstrate best practices in practice. About the team. Diverse Experiences. AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the jobdescription, we encourage candidates to apply. If your career is just starting, hasnt followed a traditional path, orincludes alternative experiences, dont let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. Wepioneered cloud computing and never stopped innovating thats why customers from the most successfulstartups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture. Here at AWS, its in our nature to learn and be curious. Our employee-led affinity groups foster a culture ofinclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our. Conversations on Race and Ethnicity (CORE) and Amaze. Con (diversity) conferences, inspire us to never stopembracing our uniqueness. Mentorship & Career Growth. Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youllfind endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop intoa 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 theworkplace and at home, theres nothing we cant achieve in the cloud. Basic Qualifications- Bachelor's degree in computer science, engineering, mathematics or equivalent- 10 years of cloud architecture and solution implementation experience, or degree in advanced technology- 7 years of hands-on experience designing, building, or advising on Machine Learning and/or AI systems in production environments- Deep understanding of the end-to-end ML lifecycle: data preparation, model training, evaluation, deployment, monitoring, and governance- Demonstrated ability to influence technical direction across organizational boundaries without direct authority- 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 architectural standards at organizational scale. Preferred Qualifications- Deep expertise in Generative AI architectures: large language models, foundation model hosting, RAG pipelines, vector databases, embedding strategies, and prompt engineering- Hands-on experience with Agentic AI patterns: autonomous agents, multi-agent systems, tool-use architectures, planning/reasoning patterns, and human-in-the-loop orchestration- Expert-level knowledge of AWS AI/ ML services: Amazon Bedrock, Amazon Sage. Maker, Amazon Q, AWS Trainium/ Inferentia, Amazon Kendra, Amazon Open. Search, and related services.- Experience defining or contributing to the AWS Well-Architected Guidance or similar enterprise-scale architectural review guidance- Recognized thought leader with a strong publication record and conference speaking history (re:Invent, AWS Summits, industry architecture conferences, or equivalent).- Experience with Infrastructure as Code (CDK, Cloud. Formation, Terraform) and CI/ CD practices for ML pipelines (ML - Ops/ LLM - Ops).- Deep knowledge of responsible AI practices: fairness, explainability, safety guardrails, governance guidance, and regulatory compliance- AWS certifications (Solutions Architect Professional, Generative AI, or equivalent).- Demonstrated experience mentoring senior engineers and contributing to organizational hiring and talent development strategy.