As a Senior Backend Engineer on the Platform engineering team , you’ll lead the development of key aspects of our core services, including data I/O, streaming and storage capabilities. In this role, you will drive the evolution of our data infrastructure , focusing on large-scale high-throughput import and export, enabling our customers to seamlessly stream data from our to their platform, supporting the development of next generation AI models. Your Day to Day Design, Develop, Deploy : Lead the design, development, and deployment of critical backend systems for large-scale distributed data infrastructure, including high-throughput exports. Scalability & Performance : Architect highly scalable, secure, and performant systems to handle billions of records at blazing speeds. Customer Collaboration : Work directly with customers to understand their needs, troubleshoot issues, and continuously improve the platform based on their feedback. Project Leadership : Drive initiatives from concept to execution, collaborating across teams and acting as a project owner. Strategic Planning : Work closely with stakeholders to define the Platform team’s roadmap and work closely with senior leadership to shape the company’s future. Innovation in AI: Contribute to building new capabilities for an AI platform used by leading AI labs to develop powerful multi-modal large language models (LLMs). About You 5-8+ years of experience as a backend software engineer Expertise in a modern programming language (Python, Java, Kotlin, or TypeScript) Proficient in multiple storage systems (Relational Databases, Key-Value Stores, Cloud Buckets, etc.) Strong understanding of architectural concepts for large-scale distributed systems Expertise in building streaming ETL pipelines Experience with asynchronous messaging systems (Kafka, Google Pub/Sub, AWS SQS, RabbitMQ) Extensive experience with one or more public cloud platforms: Google Cloud Platform (GCP) (preferred) Amazon Web Services (AWS) Microsoft Azure

Nice to Have Familiarity with ReactJS and front-end development techniques An understanding of microservices architecture Knowledge of Google Spanner and ElasticSearch Working knowledge of orchestration systems (e.g., Kubernetes) Familiarity with DevOps tools, such as ArgoCD, CodeFresh, and DataDog

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