All of it involves building agentic AI systems at production scale with real users, real constraints, and direct accountability to the customer.

Why This Role

• You'll build and deliver, not advise — you own your workstreams end-to-end. You're accountable for working software in production, not slide decks or recommendations.
• AI-native problems from day one — every engagement involves designing agents, orchestrating them, evaluating their outputs, or making them extensible. You'll work at the frontier of applied AI engineering.
• Real ownership with real stakes — you'll own the delivery of complete AI workstreams where the customer is watching. There's nowhere to hide and no shortage of interesting problems.
• Full-stack exposure — React frontends, Python services, AWS CDK infrastructure, AI agent logic. You'll touch it all, and you'll need to.
• Direct customer impact — you won't hear about customer outcomes secondhand. You'll be sitting with the customer when the system you built goes live, and you'll iterate on it together.
• Accelerated growth — you'll develop faster than in a traditional SDE role because you're solving problems end-to-end in high-pressure environments. You'll work alongside senior and principal engineers who will challenge you and expand your technical scope.
• Coaching opportunity — you'll coach customer engineers and new team members on producing high-quality code, raising the bar across every engagement.

Travel requirement: This role requires 30–50% travel.

Basic Qualifications

• Experience programming with at least one software programming language
• Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
• Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
• 3+ years of non-internship professional software development experience

Preferred Qualifications

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Experience building or deploying AI/ML applications in production environments
• Experience with agentic workflows, RAG pipelines, or foundation model integration
• Experience mentoring junior engineers
• Experience working in customer-facing or consulting-adjacent engineering roles

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page [https://www.amazon.jobs/en/privacy_page]) to know more about how we collect, use and transfer the personal data of our candidates.

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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations [https://amazon.jobs/content/en/how-we-hire/accommodations] for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.