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.

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