System Development Engineer

- Experience (non-internship) in professional software development
- Bachelor's degree in computer science or equivalent
- Experience building services using AWS products
- Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems
- Experience in automating, deploying, and supporting large-scale infrastructure
- Experience programming with at least one modern language such as Python, Ruby, Golang, Java, C++, C#, Rust
- Experience with CI/CD pipelines build processes
- 3+ years of systems development experience
- Experience automating and configuring systems using infrastructure-as-code and configuration-as-code techniques
- Experience working in an Agile environment using the Scrum methodology
- Experience with Microsoft Exchange, Postfix, or email security platforms (Mimecast, Barracuda, Proofpoint)
- Experience building production applications using Amazon Bedrock, Amazon Quick, or similar generative AI platforms
- Hands-on experience with RAG, prompt engineering, fine-tuning foundation models, or building AI agents
- Knowledge of ISO 27001, GDPR, NIS2 Directive, or similar compliance frameworks
- Experience with distributed systems, DevOps/SRE practices, and software design patterns that promote security and scalability
- Experience in PowerShell, Python, and TypeScript

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

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At Amazon, we believe that every day is "Day One." A day for the first step or to meet a new challenge, and today could be the day that you become part of a bigger idea. Come join a group of creative people that help redefine the company daily. Working for Amazon is a new excitement every day.

In Enterprise Engineering, we build the software, services, and infrastructure that enable Amazon teams across the world to do their work on a daily basis. We represent the intersection of AWS technology and the need for traditional IT solutions at Amazon's scale. We're an AWS-focused, security-obsessed, builder-centric organization, focused on using AWS technology to reshape and reinvent the traditional IT experience. We succeed when we make Amazonians around the world more effective in their work and more efficient in how they get it done.

You and your team will work with internal Amazon service owners and AWS product teams to develop new services and solutions that give enterprise IT customers more choice and self-service platforms that we offer our global workforce. You will leverage generative AI, large language models, and machine learning techniques to build intelligent automation, enhance user experiences, and drive operational efficiencies across our mailbox and messaging platforms. You will build new solutions that raise the bar for security, automation, and operational excellence.

We are looking for a motivated builder who is passionate about applying AI/ML to real-world enterprise problems at scale. This is a hands-on position where your daily activities will range from strategic planning and designing AI-powered features to new system development to supporting the customers that depend on your services. You will deliver consistent, well-defined results in an agile systems development workflow. To succeed in this role, you will deliver on-time results that delight your customers while inspiring your team to think big about their work. If this sounds like a fit, we would love to speak with you.


Key job responsibilities
• Partner with customers, stakeholders, and service owners to deliver technical solutions for complex enterprise problems at scale.
• Design, build, and integrate generative AI and machine learning solutions into mailbox and messaging platforms using AWS services such as Bedrock, SageMaker, and Quick.
• Translate complex requirements into detailed architecture and design, evaluating where AI/ML approaches can simplify or enhance solutions.
• Leverage Spec-driven development and AI-assisted development tools (code generation, intelligent testing, automated documentation) to accelerate delivery and raise engineering quality.
• Instill a DevOps culture with high-quality code reviews, automation, and operational excellence across globally scaled services.
• Provide hands-on technical leadership: guide day-to-day operations, resolve incidents, lead development activities, collaborate on architecture decisions, and carry out deployments.
• Stay current with rapidly evolving AI/ML technologies, continuously learning and applying new tools, frameworks, and foundation models to improve team processes.
• Own, support, and further develop your team's products and services, participating in an on-call rotation.
• Train/Mentor and develop engineers, providing guidance on technical best practices, code quality and effective use of AI/ML tools and techniques.