Solutions Architect III, Salesforce Account Team

Are you passionate about helping customers solve complex technical challenges and shaping their technology strategy? At Amazon, we're looking for a Solutions Architect who thrives at the intersection of business and technology. In this role, you'll partner directly with customers to design and deliver cloud-based solutions that address real business needs — from reducing costs and mitigating risk to launching new products and transforming legacy platforms. You'll bring both technical depth and practical judgment to every engagement, working to understand each customer's unique context and crafting architectures that are secure, reliable, scalable, and cost-optimized. If you're a curious, collaborative problem-solver who wants to make a measurable impact on how organizations build for the future, we'd love to hear from you.

Key job responsibilities

• Design end-to-end AI/ML solutions by combining business understanding with deep technical expertise across the ML lifecycle, model training and fine-tuning, inference, and MLOps, ensuring architectures are extensible, secure, reliable, and cost-optimized while balancing short-term needs with long-term business outcomes. Guide customers on generative AI, foundation models, and classical ML, and help them select the right approach (e.g., prompt engineering, RAG, fine-tuning, or custom model training) for their use case.
• Serve as a trusted technical advisor to customer leadership, building relationships, understanding their data and technology challenges and industry context, and guiding their AI strategy through considered options and clear articulation of trade-offs, risks, and responsible-AI considerations such as governance, bias, security, and cost.
• Lead technical AI/ML solution discussions with customer teams, diving into model selection, data pipelines, training and inference architecture, evaluation, and best practices — proactively identifying high-risk or overly complex approaches (e.g., unnecessary model training, unscalable inference patterns) and engaging the right specialist and service-team resources when needed.
• Develop and deliver technical AI/ML content such as workshops, hands-on labs, presentations, blog posts, and reference architectures that educate customers on generative AI and ML strategy and best practices, applying your depth of experience to create reusable, high-quality artifacts that accelerate adoption.
• Collaborate with internal teams across sales, engineering, professional services, science, and product groups to accelerate AI/ML solution adoption, gather customer feedback on models and services, and translate it into clear requirements that improve the AI/ML product portfolio.

A day in the life Your morning might start with a deep-dive architecture review alongside a customer's engineering team, working through design decisions for a cloud migration or a new application platform. After lunch, you could be whiteboarding a proof of concept that demonstrates how to simplify a complex workflow, then jumping into a call with product engineers to share feedback you've gathered from recent customer engagements. You'll regularly create and refine technical content, mentor fellow architects, and contribute to patterns that help the broader team deliver better solutions.

About the team Our Solutions Architecture team is dedicated to helping customers achieve their most ambitious technology goals. We work across industries and use cases, partnering closely with engineering, sales, and professional services to deliver solutions that create lasting business value. We're a collaborative group that values continuous learning, knowledge sharing, and creative problem-solving. If you're excited about working with customers to turn complex challenges into elegant solutions and want to grow your career alongside some of the most thoughtful technical minds at Amazon, this is the team for you.

• 5+ 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
• 8+ years of IT development or implementation/consulting in the software or Internet industries experience
• Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
• Experience with at least one major cloud platform and its AI/ML services (e.g., SageMaker, Bedrock, or equivalents).