Software Development Engineer II

Position: Software Development Engineer II, Amazon
Description

 SDE2 - Enterprise Foundational AI (EFAI)

How often have you had an opportunity to build technology that transforms how a global workforce operates? Are you passionate about designing and developing AI-native systems that power everyday workflows at unprecedented scale? Do you want to write code that makes every Amazonian's work life measurably better - faster, simpler, and more impactful? If so, we want to hear from you!

Enterprise Foundational AI (EFAI) accelerates Amazon's AI-native transformation by building, integrating, and scaling foundational AI products and experiences that power Amazonian productivity globally. We deliver two categories of work: (1) technical primitives - unified, secure, and intelligent building blocks that enable AI application builders to deliver faster without reinventing common capabilities, and (2) core AI products and experiences that solve end-to-end use cases highly common across Amazon and agnostic of organization or job role.

Our solutions serve 500k+ Amazonians worldwide, making AI an embedded, intuitive part of how work gets done - not a separate tool to adopt, but a native layer woven into processes, decisions, and workflows.

We're seeking a Software Development Engineer (SDE2) to design, build, and scale the platforms and services that power our foundational AI products and technical primitives. You'll work closely with engineering, product, and science teams to architect robust, high-availability systems that integrate AI capabilities seamlessly into Amazon's enterprise tools and workflows.

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Key Job Responsibilities

- Design and implement scalable, high-performance services and APIs that power EFAI's core AI products and technical primitives

- Build and maintain automation platforms and workflow engines that enable AI-native experiences across Amazon

- Develop integrations between AI capabilities and enterprise tools, enabling seamless adoption across diverse workflows

- Own the full development lifecycle - from system design and implementation to testing, deployment, and operational excellence

- Build telemetry, instrumentation, and data pipelines that measure adoption, usage patterns, and business impact of AI products

- Design and implement secure, extensible APIs and building blocks that enable AI application builders across Amazon to move faster

- Contribute to architectural decisions and drive technical solutions for complex, cross-organizational integration challenges

- Write clean, maintainable, well-tested code and conduct thorough code reviews to maintain high engineering standards

- Build tooling and infrastructure that accelerates developer productivity within the team and across partner teams

- Collaborate with science teams to operationalize AI/ML models and integrate them into production systems

- Ensure systems meet security, privacy, and compliance requirements in coordination with Legal, Privacy, and Security teams

- Troubleshoot and resolve production issues, driving root cause analysis and implementing preventive measures

# A Day in the Life

- Participate in daily standups and sprint ceremonies with the engineering team

- Design and build features for AI-powered automation platforms and workflow engines

- Write and review code, focusing on scalability, reliability, and operational excellence

- Collaborate with partner teams to define and implement integration points for EFAI primitives

- Analyze system performance and usage telemetry to identify optimization opportunities

- Prototype new capabilities that leverage emerging AI technologies (e.g., agents, MCP, LLM orchestration)

- Work with product managers and stakeholders to translate requirements into technical designs

- Investigate and resolve operational issues, contributing to on-call rotations

- Contribute to design reviews and technical documentation

- Mentor team members through code reviews and technical guidance

Key job responsibilities

Key job responsibilities

1.  Design and implement robust, scalable architectures for AI-powered applications.

2. Develop high-performance backend services to support AI model integration and data processing.

3. Create and maintain RESTful APIs for…