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 possible.

Responsibilities

• Work with customers' development, data science, and AI engineering teams to deeply understand their business and technical needs, then design solutions using 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 engagements, you will create resources to share your knowledge, such as blog posts, demos, or reference architectures. You will also help other technical teams understand how to identify AI/ML opportunities in their customer conversations. Occasionally, you may present at large events like re:Invent, get early access to new services, or advise Fortune 500 executives on multi-million dollar AI investments. Travel averages 20-30%, primarily for customer workshops, executive briefings, and AWS events.

Requirements

• Deep technical experience working 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.
• Familiarity with the GenAI ecosystem, including model providers, orchestration frameworks, vector databases, and evaluation tools.
• Strong mathematics and statistics background is preferred, along with experience in solution architecture and production ML systems.

Qualifications

Basic Qualifications

• 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.

Preferred Qualifications

• 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 their career path hasn’t followed a traditional route. The team fosters an inclusive culture where curiosity and connection drive innovation. Employee-led and company-sponsored affinity groups promote inclusion, and regular inclusion events strengthen collaboration.

Benefits

• Comprehensive benefits package.
• Sign-on payments and restricted stock units (RSUs) as part of your compensation package.
• Endless knowledge-sharing, mentorship, and career-advancing resources to help you develop professionally.
• Flexible work culture that values work-life harmony, supporting both professional success and personal well-being.