About The Position

AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and committed support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with simple API calls. AWS is looking for a genAI/ML Solutions Architect who will be the Subject Matter Expert for helping customers in the United States design solutions that leverage our GenAI services, including Amazon Bedrock, Amazon SageMaker, and Amazon Q. As part of the team, you will work closely with customers to enable large-scale use cases, design GenAI pipelines, and drive the adoption of AWS for the AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage genAI on AWS. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward.

Requirements

  • 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
  • 3+ years of design, implementation, or consulting in applications and infrastructures experience
  • 10+ years of IT development or implementation/consulting in the software or Internet industries experience
  • Deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning.
  • Familiarity with the ecosystem of software vendors in the genAI space.

Nice To Haves

  • 5+ years of infrastructure architecture, database architecture and networking experience
  • Knowledge of SAP systems (like SAP Business Suite, S/4HANA, SAP Business Warehouse, SAP HANA, SAP Business Objects, etc.) and their architecture and infrastructure needs
  • Experience working with end user or developer communities
  • Experience managing relationships with SAP customers and partners
  • Experience in SAP S/4HANA, SAP Cloud Platform, SAP Cloud ERP and Cloud ERP Private
  • Experience in SAP clean core design concepts, including design and build using non-SAP technologies in domains such as Generative / Agentic AI, and data & analytics
  • A strong mathematics and statistics background is preferred in addition to experience building machine learning models.

Responsibilities

  • Working with customers’ development and data science teams to deeply understand their business and technical needs.
  • Design solutions that make the best use of the AWS cloud platform and AWS AI/ML Services including SageMaker, Amazon Bedrock, Amazon Comprehend, Amazon Rekognition, Amazon Transcribe, Amazon Lex, Amazon Personalize, and the other AI/ML services.
  • Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and revenue attainment in the AMERICAS for Amazon SageMaker and related services that support GenAI use cases.
  • Evangelize AWS ML services and share best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
  • Act as a technical liaison between customers and the AWS SageMaker or other service teams to provide customer driven product improvement feedback.
  • Develop and support an AWS internal community of GenAI related subject matter experts in the AMERICAS.

Benefits

  • sign-on payments
  • restricted stock units (RSUs)
  • health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
  • 401(k) matching
  • paid time off
  • parental leave
  • endless knowledge-sharing, mentorship and other career-advancing resources
  • flexible working culture
  • employee-led affinity groups foster a culture of inclusion
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