AI/ML Specialist Solutions Architect, Payments, AGS US Specialist SA

About the role

AWS Global Sales drives adoption of the AWS cloud worldwide, empowering customers of all sizes to innovate and expand in the cloud. As a GenAI/ML Solutions Architect, you will serve as the Subject Matter Expert helping customers in the United States design solutions leveraging AWS GenAI and ML services. You will work as an overlay to field sales teams, covering customers across multiple verticals to architect and adopt solutions using Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker AI, Amazon Nova models, and the broader AI/ML portfolio.

You will design RAG architectures, agentic AI workflows, model customization strategies, responsible AI implementations, and production-scale inference pipelines. You will interact with other Solutions Architects in the field, providing guidance on customer engagements, and develop blog posts, reference implementations, workshops, and presentations to enable customers to fully leverage generative AI on AWS. Additionally, you will act as the voice of the customer, working closely with service teams to submit product feature requests and drive the platform forward.

Travel up to 30% across the United States may be required.

Responsibilities

• Work with customers' development, data science, and AI engineering teams to deeply understand their business and technical needs, then design solutions leveraging AWS AI/ML services such as Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker AI, Amazon Nova foundation models, Amazon Quick, Kiro, Amazon Comprehend, Amazon Rekognition, Amazon Textract, and Amazon Transcribe.
• Partner with Solutions Architects, Sales, Business Development, and AI/ML service teams to accelerate customer adoption and revenue attainment for AWS generative AI and machine learning services, with a focus on Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker AI, and the agentic AI portfolio.
• Evangelize AWS GenAI/ML services and share best practices through AWS blogs, whitepapers, reference architectures, sample code repositories, and public-speaking events such as AWS Summit and AWS re:Invent.
• Act as a technical liaison between customers and AWS service teams (Bedrock, AgentCore, SageMaker, and broader AI/ML) to provide customer-driven product improvement feedback and feature requests.
• Develop and support an AWS internal community of GenAI-related subject matter experts in the Americas, enabling field teams to identify, qualify, and position generative AI and agentic AI opportunities with their customers.

A day in the life

Most of your time is spent working directly with customers, helping them use generative AI and machine learning to solve real business problems. On a given day, you might:

• Consult with engineers at a large insurance company to design an AI agent for processing claims documents, sketching architectures and discussing data tradeoffs.
• Prepare and deliver demos for customers evaluating AWS against competitors for conversational AI use cases.
• Run on-site workshops guiding a customer's ML team through building their first retrieval-augmented generation pipeline.
• Focus on a specific industry (e.g., financial services, healthcare, manufacturing) to build deep familiarity with its problems, regulations, and data challenges.
• Work with multiple companies within your industry on engagements ranging from a few weeks to a couple of months.

Between customer conversations, you'll create resources to share your knowledge, such as blog posts, demos, or reference architectures for peers. You'll also help other technical teams understand how to identify AI/ML opportunities in their customer conversations. Occasionally, you may present customer success stories at events like re:Invent, get early access to new services to shape their development, or advise Fortune 500 executives on multi-million dollar AI investments. Travel runs about 20-30%, primarily for customer workshops, executive briefings, and AWS events.

Requirements

• 4+ years of experience in specific technology domain areas such as software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics.
• 2+ years of experience in design, implementation, or consulting for applications and infrastructures.
• Deep technical experience with generative AI, machine learning, and/or deep learning technologies.
• Hands-on experience building applications on foundation models, including RAG pipelines, agent frameworks, prompt engineering, model evaluation, and fine-tuning.
• Strong mathematics and statistics background preferred, along with experience in solution architecture and production ML systems.
• Familiarity with the GenAI ecosystem, including model providers, orchestration frameworks, vector databases, and evaluation tools.
• Experience working within software development or Internet-related industries.
• Experience migrating or transforming legacy customer solutions to the cloud.
• Experience working with AWS technologies from a dev/ops perspective.

About the team

AWS values diverse experiences and encourages candidates to apply even if they do not meet all preferred qualifications. We foster an inclusive culture where curiosity and connection drive innovation. Our employee-led and company-sponsored affinity groups promote inclusion, and our inclusion events build stronger, more collaborative teams. Continual innovation is fueled by bold ideas, fresh perspectives, and passionate voices.

Benefits

• Comprehensive benefits package.
• Sign-on payments and restricted stock units (RSUs).
• Endless knowledge-sharing, mentorship, and career-advancing resources to help you develop into a better-rounded professional.
• Flexible work culture valuing work-life harmony.