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AI Engineers in AWS AI Engineering help customers build and use AI agents to transform how work gets done. You will design and productionize agentic systems using services like Amazon Bedrock and AgentCore, contribute to open-source AI accelerators, and help customers adopt AI-native software development practices.
The role splits roughly 50/50 between direct customer engagements and building leverage through reusable assets, open source, and thought leadership. In customer work, you will partner with software development teams to leverage AI coding tools like Kiro, Claude Code on Bedrock, and Codex on Bedrock. You'll work hands-on to unblock adoption and ensure solutions are secure, reliable, and cost-effective. In your building time, you will create reference implementations, contribute to open-source projects, and develop content that enables the broader community. You will work closely with AWS product teams to close the loop between what customers need and what AWS builds.
This is a global role within the Solutions Architect organization. You will maintain deep relationships with AI product teams and collaborate with specialists across regions to stay current on capabilities and influence roadmaps.
Key job responsibilities As an AI Engineer, you will lead customer technical engagements from initial problem framing through production readiness, working hands-on to design and deploy agentic systems using Amazon Bedrock, AgentCore, and other AWS services. You will help customers design effective tool schemas, implement memory patterns, and build evaluation pipelines that catch failures before production. A core part of the role involves creating reusable open-source assets, templates, and reference implementations that accelerate adoption across the broader developer community. You will partner with AWS service teams to close the feedback loop between field learnings and product improvements, ensuring customer friction translates into platform enhancements. Finally, you will represent AWS credibly with developer audiences through technical talks and thought leadership, sharing practical guidance grounded in production experience. You will be an expert in driving AI coding tool adoption across software development teams, and have deep expertise across the entire software development lifecycle.
A day in the life You might start your morning debugging a customer's agent that's hitting context limits, then spend the afternoon reviewing a pull request for an open source project. Later, build something with the latest model and coding agent releases to stay up-to-date through hands-on building. Some days you're on-site pair-programming with a customer's engineering team; others you're preparing a talk for an upcoming conference. The work varies, but you'll always be deep with hands-on building and direct customer impact.
About the team AI Engineering is a global team within the Solutions Architect organization focused on helping customers build and use AI agents. We operate at the frontier of AI, bridging foundation models and production systems through direct customer engagements, open-source accelerators, and close collaboration with AWS service teams. We split time between hands-on customer work and creating assets that scale. The role combines engineering, advisory work, and product influence. We maintain high standards while operating with speed, and we stay grounded in customer outcomes. Built for tinkerers who ship production code and thrive in ambiguity.
Basic Qualifications
- 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 3+ years of design, implementation, or consulting in applications and infrastructures experience
- 10+ years of IT development or implementation/consulting in the software or Internet industries experience
- Experience presenting to both technical and non-technical executive audiences
- Experience leading or developing high quality, enterprise scale software products using a structured system development lifecycle
- Knowledge of software development tools and methodologies
Preferred Qualifications
- 5+ years of infrastructure architecture, database architecture and networking experience
- Experience working with end user or developer communities
- Experience in SAP clean core design concepts, including design and build using non-SAP technologies in domains such as Generative / Agentic AI, and data & analytics
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