Join a pioneering team transforming safety decision-making for Amazon's Delivery Service Partners (DSPs) across 21 countries. We are building an intelligent, data-driven platform dedicated to protecting delivery associates daily. DSP SafetyTech acts as the crucial intelligence layer, interpreting safety signals and ensuring every event is addressed.

This role offers a unique opportunity to contribute to building a governed safety intelligence platform from its foundation. You will play a key part in developing three core components: Safety Data as a Service (SDaaS) for consolidated data, DSP Facing Mechanisms for rule management, and Advanced Analytics for predictive insights and AI agents.

Be part of an initiative that directly impacts the safety of delivery associates globally. This is your chance to innovate and build a critical system from the ground up.

Design, develop, and deploy software components for a unified data serving platform, consolidating diverse safety data sources. Build and maintain robust backend services and APIs that manage intricate safety business rules.

Develop frontend components for a comprehensive safety dashboard, providing a single, actionable view of safety metrics. Implement advanced safety signals to create higher-level indicators from raw data.

Write clean, maintainable, and well-tested code, adhering to software engineering best practices. Engage in code reviews, design discussions, and contribute to operational excellence. Collaborate with data engineers and scientists to integrate models and pipelines into production services.

Assist in developing automated evidence preservation mechanisms and troubleshoot production issues, including participating in on-call rotations. Work closely with cross-functional teams to gather requirements and deliver impactful solutions.

We seek an experienced Software Development Engineer with a minimum of 3 years of professional software development experience, excluding internships. A strong background of at least 2 years in designing or architecting new and existing systems, including patterns, reliability, and scaling, is essential.

Proficiency in at least one software programming language is required. A background encompassing the full software development lifecycle, including coding standards, code reviews, source control, build processes, testing, and operations, is highly valued.

Experience with cloud environments and distributed systems is beneficial. A Bachelor's degree in Computer Science or a related field is preferred. Familiarity with data engineering principles and AI/ML concepts would be an advantage.