Sr Solutions Architect GenAI, Automotive & Manufacturing GenAI

In this role, you will partner with automotive and manufacturing customers to design scalable generative AI architectures on AWS, translating business needs into technical solutions. You’ll influence AI roadmaps, collaborate with cross-functional teams, and craft demos and POCs that demonstrate measurable value. You’ll mentor peers, share best practices, and represent AWS at events to advance adoption of our AI stack. You help organizations achieve transformation through enterprise-scale, trustworthy AI systems.

• Develop strategic technical roadmaps and implementation plans for generative AI solutions aligned with customer objectives
• Design and implement generative AI architectures that orchestrate complex workflows across enterprise systems using AWS services like Amazon Bedrock, SageMaker, Kiro, and Amazon Quick
• Advise senior technical and executive stakeholders on architectural trade-offs and long-term AI strategy in business terms
• Mentor team members and contribute to internal knowledge sharing on AI adoption best practices
• Lead thought leadership and evangelize AWS generative AI capabilities through public speaking, blogs, and reference architectures
• Stay current with advancements in generative AI and AWS offerings to optimize performance and technology choices
• Define evaluation frameworks for AI systems, including model benchmarking, output quality, and operational monitoring (AIOps) to meet reliability and governance standards
• Review customer requirements to identify opportunities for AI-driven transformations and develop compelling proof-of-concepts
• Influence service leadership and product marketing on future needs, prioritizing roadmap features and GTM messaging
• Dedicate time to continuous learning and knowledge sharing to enable broader field adoption of generative AI solutions

• Experience in technology domains such as software development, cloud computing, systems engineering, or data & analytics
• Experience in design, implementation, or consulting for applications and infrastructures
• Experience communicating across technical and non-technical audiences, including executives

• Strong interpersonal and communication skills
• Mentorship and knowledge-sharing abilities
• Public speaking and thought leadership
• Experience with AWS AI services (Amazon Bedrock, SageMaker, Kiro, Amazon Quick)
• Experience designing, deploying, and evaluating LLM-powered agents and orchestration
• AI system evaluation methodologies, LLM evaluation frameworks, automated testing pipelines, and AIOps for monitoring at scale