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 content such as 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 platform improvements.

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 using AWS AI/ML services including 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 solve real business problems using generative AI and machine learning. Engagements may include:

• Video calls with engineering teams to architect AI solutions, such as an AI agent for processing claims documents.
• Preparing demos for customers evaluating AWS for conversational AI use cases.
• On-site workshops guiding customers through building retrieval-augmented generation (RAG) pipelines.
• Focusing on a specific industry (e.g., financial services, healthcare, manufacturing) to build expertise in its unique challenges, regulations, and data requirements.

Between customer engagements, you create reusable content such as blog posts, demos, or reference architectures to share knowledge with peers. You also help other technical teams identify AI/ML opportunities in their customer conversations. Occasionally, you may present at large events like re:Invent, shape new services based on customer feedback, or advise Fortune 500 executives on AI strategy. Travel averages 20-30% for customer workshops, executive briefings, and AWS events.

Requirements

• 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.
• Familiarity with the GenAI ecosystem, including model providers, orchestration frameworks, vector databases, and evaluation tools.
• Strong mathematics and statistics background (preferred).
• Experience with solution architecture and production ML systems.

Qualifications

Basic Qualifications

• 4+ years of experience in technology domains such as software development, cloud computing, systems engineering, infrastructure, security, networking, data, or 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 DevOps perspective.

About the team

AWS values diverse experiences and encourages candidates from all backgrounds to apply, even if their career path hasn’t followed a traditional trajectory. The team fosters an inclusive culture where curiosity and connection drive innovation. Employee-led affinity groups and inclusion events promote collaboration and empower individuals to bring their unique perspectives to their work.

Benefits

• Comprehensive benefits package.
• Sign-on payments and restricted stock units (RSUs).
• Endless knowledge-sharing, mentorship, and career-advancing resources.
• Flexible work culture valuing work-life harmony.