Senior Cloud Architect, Machine Learning and AI

Job Overview

Join the global Forward Deployment Engineering team to design and implement production-grade ML and Generative AI solutions on AWS, acting as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale. Translate complex business problems into secure, reliable, cost-efficient, and observable cloud architectures. Evolve internal and customer AI/ML usage by creating reusable patterns that influence the product roadmap. Depending on needs, focus on Field Engineering (pre-sales and GTM) or FDE Delivery (install base, product adoption, and customer health).

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 (security, reliability, performance, cost).
• Provide opinionated guidance on GenAI architectures (e.g., Amazon Bedrock, SageMaker, Q) and integration with existing systems and processes.
• For Field Engineering: Partner with teams to shape and win opportunities, lead technical 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 issues, and participate in account-team routines to align AI/ML architectures with goals.
• Help evolve AI/ML usage internally and with customers by turning solutions into reusable patterns and influencing the product roadmap.

Qualifications

• Expertise in leading design and implementation of production-grade ML and Generative AI solutions on AWS, with awareness of multi-cloud environments.
• Experience as a hands-on expert and trusted advisor for customers with 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 motions.
• For Delivery: Experience in install base health, product adoption, proactive engagements, and account-team collaboration.