Solutions Architect, AI - Manufacturing and Life Science

Role Overview

Solutions Architects at Amazon Web Services (AWS) build technical relationships with customers of all sizes and operate as their trusted advisor. In this role you will work with AWS customers and industry domain experts to create the architectures for solutions to Retail and Consumer Goods industry challenges, design and build these solutions, and continue to refine and scale them by working closely with AWS Professional Services, AWS Partners, and customers.

This role requires hands‑on experience in application integration design, solid knowledge of business software application design stemming from domain‑driven design, and micro‑services and component‑based architectures. It also benefits from expertise in applied AI and the deployment of industry solutions, as well as insights into how cloud‑based software solutions are built, including handling of sensitive data, process observability, and audit readiness.

This role will include up to 30% travel.

• Work with AWS customers and industry domain experts to create architectures for Retail and Consumer Goods industry challenges.
• Design and build solutions, and continue to refine and scale them with AWS Professional Services, AWS Partners, and customers.
• Apply application integration design, domain‑driven architecture, micro‑services, and component‑based architectures to solve customer problems.
• Participate in the creation and sharing of best practices, technical content, and new reference architectures such as white papers, code samples, and blog posts.
• Evangelize and educate about AWS technology and industry trends through workshops, user groups, meetups, public speaking, online videos, or conferences.

• 8+ years of experience in specific technology domain areas (e.g., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
• Experience leading or developing high‑quality, enterprise‑scale software products using a structured system development lifecycle.
• Experience communicating across technical and non‑technical audiences, including executive‑level stakeholders or clients.
• Knowledge of cloud architecture.

• Experience working with end‑user or developer communities.
• Knowledge of software development tools and methodologies.
• Experience with Generative AI and agentic AI solutions in enterprise contexts.