Senior Solutions Architect, AI-Applied Guidance, Well-Architected Solutions Innovation

Senior Solutions Architect AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset. 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 Senior 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. 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 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 AI-assisted 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 Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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. 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. 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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 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. Basic Qualifications - Bachelor's degree in computer science, engineering, mathematics or equivalent- 7+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience- 3+ 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 - Knowledge of AWS services, market segments, customer base and industry verticals- 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 SageMaker, Amazon Q, AWS Trainium/Inferentia, Amazon Kendra, Amazon OpenSearch, 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, CloudFormation, Terraform) and CI/CD practices for ML pipelines (MLOps/LLMOps).- 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 A W S