Solution Architect, Amazon

• 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• 2+ years of design, implementation, or consulting in applications and infrastructures experience
• 5+ years of IT development or implementation/consulting in the software or Internet industries experience
• AWS 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

Desirable

• As part of the GenAI Platform team, you'll develop and deploy strategies to accelerate customer adoption across industry verticals. You'll work directly with key customers on GenAI model training and inference, helping them adopt and scale large-scale workloads like foundation models, conduct performance evaluations, and develop demos and GTM plans
• AWS Specialist Solution Architects(SSA) are technologists with deep domain expertise and business development acumen to solve customers' most complex challenges through scalable, flexible technical architectures
• As members of Area Specialist and Account Teams, SSAs guide customers through application refactoring and cloud-based system designs while handling account planning and opportunity pursuit, bringing valuable insights to product teams and strengthening the roadmap
• Drive business development through market sizing, pipeline building, and technical proof-of-concept requirements with customers
• Develop and execute GTM plans by working directly with customers to understand business problems and implement scalable GenAI solutions
• Develop cloud-based GenAI solutions enabling customers to build and deploy workloads on EC2, SageMaker Hyperpod, and accelerated compute platforms
• Create technical architectures, content, and enablement materials to train field teams and establish thought-leadership
• Collaborate with account teams, research scientists, product teams, ISVs, and model providers to drive implementations and innovation
• Communicate GenAI potential and technical challenges to engineering teams and C-Level executives, leveraging expertise in GPU based compute infrastructure and ML frameworks
• Identify cross-industry patterns and trends to accelerate innovation and represent AWS best practices to customers and partners