Solutions Architect, Knowledge Management & Governance, Worldwide Field Enablement

Join our team as a Solutions Architect where you'll pioneer the future of AI‑driven enablement at scale. This isn't your typical SA role—you'll architect intelligent systems that fundamentally transform how we analyze, design, develop, implement, and evaluate enablement programs across our global organization.

You'll be building the AI infrastructure that reduces program development cycles by 40% while improving quality and field outcomes. Rather than supporting existing systems, you'll design and implement modern AI agents and automation solutions that haven't been built before. You'll work at the intersection of instructional design, change management, and artificial intelligence—creating solutions that diagnose skill gaps, orchestrate practice, deliver feedback, and reinforce execution where work actually happens.

You'll solve the challenge of scaling personalized learning experiences across thousands of users while maintaining quality and pedagogical rigor. You'll address the complexity of integrating AI capabilities across Analysis, Design, Development, Implementation, and Evaluation phases—ensuring our AI investments deliver measurable ROI rather than joining the 95% of AI pilots that fail.

Key Responsibilities

• Architect AI‑powered enablement systems that automate content analysis, design recommendations, and development workflows, reducing time‑to‑delivery by up to 40%.
• Build intelligent agents for knowledge management and governance that provide scalable, adaptive support across the entire content lifecycle.
• Create workflow‑integrated solutions that deliver contextual guidance and just‑in‑time learning directly within existing tools and processes.
• Establish technical foundations for human‑AI collaboration frameworks that balance automation with strategic human oversight to implement enablement initiatives.

Basic Qualifications

• Experience with one of the following programming languages: Python, Ruby, Node.js, C#, or C++.
• Experience in any of the following: Cloud Architecture, Systems Design, Software Development, Infrastructure Architecture, Data Engineering or DevOps.
• Demonstrated experience in prompt engineering for large language models (LLMs), including designing, testing, and optimizing prompts to achieve specific outcomes in AI‑powered applications and workflows.

Preferred Qualifications

• Experience implementing a cloud‑based technology solution.
• Knowledge of AWS services, such as Elastic Compute Cloud (EC2), Elastic Block Storage (EBS), and Simple Storage Service (S3).

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.