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 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 blogs, whitepapers, reference architectures, sample code repositories, and public-speaking events (e.g., AWS Summit, 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 internal AWS community of GenAI-related subject matter experts in the Americas, enabling field teams to identify, qualify, and position generative AI and agentic AI opportunities.

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. Engagements may include:

• Video calls with engineering teams to sketch architectures (e.g., AI agents for claims processing in insurance).
• Preparing demos for customers evaluating AWS against competitors for conversational AI use cases.
• On-site workshops guiding customers through building retrieval-augmented generation (RAG) pipelines.
• Focusing on a single industry (e.g., financial services, healthcare, manufacturing) to build familiarity with its challenges, regulations, and data needs.

Between customer conversations, you’ll create resources to share knowledge, such as blog posts, demos, or reference architectures. You’ll also help other technical teams spot AI/ML opportunities in their customer conversations. Occasionally, you may present at events like re:Invent, shape new services based on customer feedback, or brief Fortune 500 executives on agentic AI. Travel averages 20-30% for 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 (model providers, orchestration frameworks, vector databases, evaluation tools) to help customers evaluate tradeoffs and accelerate AI adoption.
• A 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 technology domains 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 from non-traditional career paths to apply. Our inclusive culture promotes collaboration through employee-led affinity groups and inclusion events, fostering innovation and professional growth.

Benefits

• Comprehensive benefits package.
• Sign-on payments and restricted stock units (RSUs).
• Mentorship and career growth resources to develop into a well-rounded professional.
• Work-life balance with flexibility to support personal and professional harmony.