Senior Cloud Architect, ML/AI

Job Overview

As part of the global Forward Deployment Engineering team, this role involves leading the design and implementation of production-grade ML and Generative AI solutions on AWS, acting as a hands-on expert and trusted advisor for customers with AI/ML workloads. Depending on business needs, the focus may be on Field Engineering (pre-sales and GTM) or FDE Delivery (install base, product adoption, and customer health), translating business problems into secure, reliable, cost-efficient cloud architectures and evolving AI/ML patterns internally and with customers.

Responsibilities

• Lead discovery, architecture, and implementation for advanced ML and Generative AI workloads on AWS, including data, training, inference, and integration layers.
• Own technical success of engagements by defining outcomes, making tradeoffs visible, and ensuring production-ready designs for security, reliability, performance, and cost.
• Provide opinionated guidance on GenAI architectures like Amazon Bedrock, SageMaker, and Q, integrating with customers’ systems and processes.
• For Field Engineering: Partner with sales teams to shape and win opportunities, serve as technical lead for POVs and CloudBuild engagements focused on AI/ML and GenAI, and build technical narratives and demos for revenue-generating motions.
• For Delivery: Act as named technical advisor for customer portfolios, lead proactive engagements to unblock AI/ML issues, and participate in account-team routines to align architectures with goals.
• Help evolve AI/ML usage internally and with customers by turning solutions into reusable patterns influencing the product roadmap.

Qualifications

• Experience leading production-grade ML and Generative AI solutions on AWS, with awareness of multi-cloud environments.
• Hands-on expertise in AI/ML workloads at scale, from discovery to deployment and optimization.
• Ability to translate complex business problems into secure, reliable, cost-efficient, and observable cloud architectures.
• For Field Engineering: Skills in pre-sales, POVs, CloudBuild engagements, and partner-led growth.
• For Delivery: Experience in install base health, product adoption, proactive engagements, and account-team collaboration.