Do you want to lead a team that defines how the world's largest enterprises build, scale, and run generative AI in production? Are you energized by the full GenAI lifecycle, from model selection and customization to inference optimization on accelerators, agentic architectures, and the evaluation and governance that make AI trustworthy at scale? Amazon Web Services (AWS) is looking for a senior technical leader to build and lead a team of specialist Solutions Architects focused on Generative AI within our Strategic Accounts organization. Your team will help customers across the GenAI stack: choosing and customizing foundation models, optimizing training and inference on AWS Trainium, Inferentia, and GPU infrastructure, building agentic systems with Amazon Bedrock, Amazon Bedrock AgentCore, and Amazon SageMaker AI, and putting in place the evaluation, guardrails, and responsible AI practices that move GenAI from pilot to production. This is a strategic leadership role. You will set technical direction for your team, architect alongside them on the most complex engagements, coach them through conversations with CAIOs, CTOs, and VPs of Engineering, and develop the prescriptive points of view that position AWS as the GenAI strategy partner for our largest customers. You will shape solutions in a space that is changing every quarter and bring customer signals back to AWS service teams to influence roadmaps. Key job responsibilities Set technical vision and strategic direction for a team of specialist Solutions Architects spanning foundation models, AI infrastructure, and agentic AI Engage directly with customer CAIOs, CTOs, and VPs of Engineering as a strategic advisor on GenAI strategy, model selection, inference economics, and production patterns for agents Architect solutions alongside your team for complex customer environments spanning model customization, distributed training, inference optimization, retrieval augmented generation, and multi-agent systems Guide customers on evaluation, observability, security, and responsible AI so GenAI workloads can scale with confidence Hire, onboard, and develop senior technical talent, and build a diverse and inclusive team culture that attracts and retains top performers Coach team members on architectural thinking, strategic customer engagement, and executive communication in the GenAI domain Develop prescriptive architectures, reference implementations, and competitive positioning that help the broader field SA community lead GenAI conversations with their customers Represent the team externally through conference presentations, published architectures, and technical keynotes that establish AWS credibility in generative AI and AI infrastructure Partner with AWS service teams (Amazon Bedrock, Amazon SageMaker AI, Annapurna Labs, compute) to shape product roadmaps based on customer signals and emerging trends Collaborate with peer SA leaders, Professional Services, the Generative AI Innovation Center, and partners to deliver unified GenAI solutions from proof of concept to production Drive engagement and contribution across open source GenAI ecosystems, including model serving, agent frameworks, and protocols such as MCP, where it accelerates customer outcomes and builds community trust A day in the life You might start the morning reviewing an inference architecture for a customer serving foundation models on Trainium clusters, looking for ways to bring down latency and cost per token. Then you join a call with the CAIO of a top-25 enterprise to talk through how they'll move a set of agent pilots into production with the right evaluation and guardrails in place. After lunch, you coach a team member who is getting ready for a customer workshop on fine-tuning and distilling models in Amazon Bedrock. Later, you finish a conference talk on design patterns for multi-agent systems that run reliably at enterprise scale. You end the day with your peer leaders, aligning on a shared customer whose GenAI program now covers several lines of business. About the team This role sits within the AWS Strategic Accounts Specialist Solutions Architecture organization. The Data & AI organization works across the full modern AI stack: from lakehouse and streaming architectures, through training and inference infrastructure on accelerators, to the semantic and context layers that make production AI reliable and agentic systems trustworthy. You will own a team charter within this organization, with room to shape its direction as customer needs and the technology landscape evolve. AWS values diverse experiences. Even if you do not meet all of the qualifications listed in this description, we encourage candidates to apply. If your career is just starting, has not followed a traditional path, or includes alternative experiences, don't let it stop you from applying.