Builder Solution Architect, AWS Product Marketing Demo Engineering

About the Role

Join the AWS Product Marketing Demo Engineering team as a Builder Solution Architect! This role focuses on designing and implementing production-quality technical demonstrations for service launches, events, sales enablement, and experiential activations across AWS services.

Key Job Responsibilities

• Design and implement production-quality technical demonstrations for service launches, events, sales enablement, and experiential activations across AWS services.
• Develop high-quality code artifacts including demos, sample code, and starter projects.
• Support responses to critical analyst evaluations such as Gartner Magic Quadrant and Forrester Wave assessments.
• Contribute to demo standards and best practices, collaborating with team members to maintain bar-raising quality in project structure, coding, and testing.
• Partner with field teams, GTM teams, service teams, and cross-functional stakeholders to understand use cases and develop demonstration solutions.
• Share knowledge through internal forums, AWS blogs, and reference architectures; contribute to enablement materials that help teams integrate AWS solutions into customer architectures.

About the Team

The AWS Product Marketing Demo Engineering team is at the forefront of showcasing AWS's transformative impact on customers and industries. We create high-quality technical demonstrations that inspire, from CEO keynote demos at re:Invent to immersive experiential activations at major industry conferences and trade shows. We create production-quality demos for AWS's highest-priority and most visible product launches—spanning generative AI, agentic solutions, and critical infrastructure.

As a Demo Engineering SA, you'll work on innovative projects, collaborating with team members to create showcases for new products and features. You'll apply your software development skills to tackle projects with ambiguous problem statements, moving quickly as you work with field team stakeholders to develop use cases and solutions. You should be comfortable learning new concepts and tools quickly and contributing across different levels of the technology stack.

Basic Qualifications

• 2+ years of design, implementation, or consulting in applications and infrastructures experience
• 4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
• Understanding of Generative AI and Machine Learning frameworks, concepts, and technologies
• Proficiency in CDK, Python, TypeScript and in programming languages and tools relevant to AI/ML and cloud development

Preferred Qualifications

• Experience collaborating with cross-functional teams, including field teams, Go-To-Market teams, and product teams
• Public speaking skills with a willingness to develop experience presenting at internal and industry events
• Ability to support innovation initiatives in evolving and ambiguous environments
• Eagerness to learn from senior team members and contribute to team norms and standards
• Experience working on code-based solutions for various GenAI use cases

Pay

• USA, CA, SANTA CLARA - 151,000.00 - 204,300.00 USD annually
• USA, CA, San Francisco - 151,000.00 - 204,300.00 USD annually
• USA, WA, Seattle - 131,300.00 - 177,600.00 USD annually

Benefits

Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Your Amazon package will also include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

This response is AI-generated, for reference only.