AI Specialist Solutions Architect, AGS US Specialist SA, FSI

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., Working with customers' development and data science teams to deeply understand their business and technical needs. After understanding their needs, you will 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. Thought Leadership - 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.

You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building machine learning models. You will be familiar with the ecosystem of software vendors in the genAI space, and will leverage this knowledge to help AWS customers in their selection process., 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

Preferred Qualifications

• 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

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the 8 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.

Why AWS? 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.

Inclusive Team Culture 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 (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth 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.

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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

About the team Diverse Experiences

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.

Why AWS?

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.

Inclusive Team Culture

AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship & Career Growth

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.

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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve., The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, NY, New York - 169,000.00 - 228,600.00 USD annually

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. Join us and help us grow. Are you passionate about Artificial Intelligence, Machine Learning, and GenerativeAI? Are you passionate about helping customers build solutions leveraging the state-of-the-art genAI/ML tools on Amazon Web Service (AWS)? Come join us! 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. Amazon.com's recommendations engine is driven by machine learning, as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition with deep learning; as is Prime Air. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it's a big part of our heritage.