Senior Specialist Solutions Architect, Amazon Quick

In this role you drive the design of scalable, cloud-based architectures at the intersection of data analytics and generative AI. You’ll collaborate with field teams to translate customer needs into AI-enabled, data-driven solutions that deliver measurable outcomes. You act as a thought leader, shaping adoption of Amazon Quick and related BI capabilities while evangelizing best practices and contributing to a global community of engineers and field experts. This is a hands-on, customer-facing technical leadership role with broad impact across customers and AWS teams.

• Lead technical solution discussions translating business needs into scalable architectures with measurable outcomes
• Design end-to-end customer solutions leveraging Amazon Quick capabilities (agentic features, dashboards, automation)
• Collaborate with field sales, training, and support to ensure customer success
• Drive customer feedback to product/engineering to influence roadmap and features
• Partner with Go-To-Market specialists to develop adoption strategies and engage customers
• Capture and share best practices, reference architectures, and patterns across the AWS solution architect community
• Create and deliver technical content (white papers, blogs, reference architectures, workshops) to educate on BI and generative AI
• Publicly evangelize AWS services and speak at events (AWS Summits, re:Invent)

• Experience in design, implementation or consulting in applications and infrastructures
• Fluency in English (spoken, written, reading)
• Experience with or evaluation of AI systems
• Experience in data and analytics domain with a focus on business intelligence
• Experience developing dashboards with BI platforms (e.g., Quick Sight, Tableau, PowerBI, Looker, Thoughtspot, Microstrategy, Sisense, Domo)

• Strong communication across technical and non-technical audiences, including executives
• Collaborative mindset and ability to work cross-functionally
• Adaptability and willingness to share knowledge through writing and speaking
• SQL and data engineering fundamentals
• Experience with BI and analytics tools (one or more listed)
• Programming knowledge (Python, Java, C++)