Senior Machine Learning Software Development Engineer, AI Ops Integration

As part of AI Operations Integration we have a vision to transform Amazon Operations & Supply Chain into an AI-Native organization by delivering intuitive and differentiated AI solutions that solve enduring operational challenges. We blend vision with curiosity and Amazons real-world experience to build rapidly AI capabilities. We accelerate our customers businesses: internal operations teams across Amazons global footprint through delivery of predictive analytics LLMs and autonomous AI agents to automate decision-making across Amazons global operations and supply chain.

As a Machine Learning Software Development Engineer youll design and deploy production ready systems that combine traditional ML with modern agentic architectures to solve impactful operational problems at scale.

This role combines the excitement of a startup environment with the scale of Amazon Operations. Youll research state-of-the-art open source and internal tools and will tackle highly ambiguous problems. If you thrive on ownership and dealing with ambiguity passionate about AI and want to fundamentally influence how Amazon Operations leverages AI this role offers an extraordinary opportunity to make your mark.

Key job responsibilities
What youll do:
Lead the technical design and architecture of production ML/LLM systems end-to-end from data pipelines and model serving to scalable user-facing applications
Architect and build agentic AI solutions that orchestrate complex operational workflows across multiple systems APIs and decision points
Define the technical strategy for internal tooling. Designing front-end platforms (dashboards products) that serve non-technical operations users at worldwide scale
Own the integration architecture across internal systems databases and MCP servers: establishing patterns that enable modular multi-system orchestration
Drive engineering excellence across the ML lifecycle: set standards for experimentation deployment monitoring evaluation and incident response
Design guardrails evaluation frameworks and human-in-the-loop architectures that ensure production AI systems operate safely and reliably at scale
Mentor junior engineers conduct design reviews and raise the technical bar across the team
Partner with scientists product managers and operations leaders to translate ambiguous business problems into well-scoped technical solutions with clear delivery milestones

About the team
Were a cross-functional team of machine learning engineers ML & AI scientists and Technical PM focused on automating operational decisions in Amazons supply chain.

Our charter is to identify high-impact automation opportunities build AI agents that can handle them reliably and deploy these systems into production
where they process real decisions daily.

The team operates with a build-measure-learn cycle. We work closely with operations partners to understand their problems prototype solutions quickly measure impact rigorously and iterate based on real-world performance.

- Bachelors degree
- Experience as a mentor tech lead or leading an engineering team
- Experience in professional non-internship software development
- Experience leading the architecture and design (architecture design patterns reliability and scaling) of new and current systems
- Experience programming with at least one modern language such as Java C or C# including object-oriented design

- Masters degree in computer science or equivalent
- Experience with full software development life cycle including coding standards code reviews source control management build processes testing and operations

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