Software Development Engineer II, AWS Invoicing

Description

AWS is expanding into more markets around the world than ever before, and the bottleneck is not customer demand — it is launch speed. Our mission is to make every new market launch faster, more reliable, and ultimately automatic — building the next-generation automation platforms that fundamentally change how quickly AWS can reach customers in new countries.

Our platforms are powered by generative AI, large language models, knowledge graphs, and agentic architectures that dynamically compose specialized agents based on context. We apply these capabilities across three reinforcing areas: intelligent launch readiness — where autonomous AI agents analyze, generate, and validate the information needed to go live in a new market; cloud-native service orchestration — where configuration-driven microservices replace per-launch bespoke engineering with centralized, reusable capabilities so that expanding into a new country becomes a zero-code configuration change rather than a development cycle;

and continuous validation — where self-healing autonomous workflows manage the full validation lifecycle from planning through execution to intelligent failure diagnosis. These three platforms feed into each other — the generative AI layer drives the orchestration layer, and the validation framework validates both, creating a closed-loop feedback system that improves accuracy and reliability with every launch. Together, they compress what has historically been a multi-month launch process into a matter of weeks.

We are looking for engineers who can help us build the platforms and tooling that will scale AWS's global expansion by an order of magnitude — with a growing backlog of market launches and a committed pipeline ahead.

• Design and build agentic AI systems that analyze, generate, and validate launch information across multiple countries, enabling domain experts to review in hours what previously took weeks.
• Build agentic architectures that compose specialized AI agents dynamically, enabling rapid iteration without code deployments and continuous learning from expert feedback.
• Architect configuration-driven pipelines so that launching a new market requires a config change, not a development cycle.
• Partner with engineers across service teams to make integration points configurable and testable by design, creating one-time investments that pay off on every subsequent launch.
• Build AI-driven continuous validation frameworks powered by agentic workflows and large language models that autonomously manage the full validation lifecycle.
• Collaborate with cross-functional stakeholders to close the feedback loop between AI-generated output and domain expertise.

• Have built or contributed to AI/ML systems in production — agentic workflows, LLM pipelines, knowledge graphs, or retrieval-augmented generation — and know the difference between a demo and a system experts trust.
• Think in systems — how configuration propagates across services, how validation maps to launch readiness, and how failures surface to the right team.
• Are comfortable with ambiguity, making architectural decisions with incomplete information and iterating based on real results.
• Write clean, testable code and care about operational excellence on systems that sit on the critical path of AWS's global expansion.
• Prefer partnering with another team to solve a problem at the source over building a workaround on your side.
• Want measurable impact — we track launch velocity, automation coverage, accuracy, and defect reduction.

• Every launch you accelerate opens a new market for AWS.
• You'll work across a state-of-the-art AI-powered platform that spans launch readiness, service orchestration, and continuous validation — not just one slice.
• We build AI systems that experts use daily and measure success by whether they trust the output enough to stop doing it manually.
• You'll spend real time understanding adjacent systems and codebases, not just calling their APIs.

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