Senior Backend Engineer, Labelbox

• Bachelor’s degree in Computer Science, Data Engineering, or a related field. Advanced degree preferred
• 4+ years of work experience in a software or data-focused company, with significant expertise in data infrastructure and backend engineering
• Deep knowledge of designing and managing scalable database systems, including relational databases (e.g., PostgreSQL, MySQL), NoSQL stores (e.g., MongoDB, Cassandra), and cloud-native solutions (e.g., Google Spanner, AWS DynamoDB)
• Strong experience with data infrastructure components such as data pipelines, streaming systems, and storage architectures (e.g., Cloud Buckets, Key-Value Stores)
• Proficiency in optimizing databases for performance (e.g., schema design, indexing, query tuning) and integrating them with broader data workflows
• Previous experience with distributed systems tools (e.g., queues, message brokers like Kafka or RabbitMQ, job orchestration frameworks) for real-time data processing and other use cases.
• Previous experience with search engines (e.g., ElasticSearch)
• Knowledge of backend development using languages like Python, Java, or TypeScript; familiarity with NodeJS and NestJS is a plus
• Proficient in data structures, algorithms, and system design for large-scale data management
• Demonstrated ability to keep up with trends in data infrastructure and database technologies
• Excellent communication and collaboration skills
• Strong sense of ownership and ability to thrive in a fast-paced environment
• Comfortable with ambiguity, breaking down high-level requirements into actionable data infrastructure tasks methodically
• Resourceful problem-solver with attention to detail, eager to take initiative and deliver results
• High proficiency in leveraging AI tools for daily development (e.g., Cursor, GitHub Copilot)

Desirable

• As a Backend Engineer, AI Data Platform at Labelbox, you will lead the design and development of our core data infrastructure, powering the seamless flow, storage, and processing of data for our AI platform
• Your expertise will drive the evolution of scalable systems—anchored by high-performance databases—to support large-scale workflows, high-throughput data I/O, and streaming capabilities
• You’ll enable Labelbox customers to efficiently manage and stream data for training next-generation AI models
• Owning critical components of our data infrastructure, including database architecture, you’ll work end-to-end on projects from design to deployment
• Collaborating cross-functionally with stakeholders, you’ll transform ideas into robust, scalable solutions that enhance platform adoption and customer success
• Design and build scalable data infrastructure, integrating high-performance databases (relational, NoSQL, cloud-native) with distributed systems for data processing, storage, and streaming
• Optimize database systems for performance, reliability, and scalability, ensuring efficient data retrieval, indexing, and querying to support AI workflows
• Develop and maintain data pipelines using distributed queues, message brokers, and job management mechanisms to enable high-throughput import/export operations
• Collaborate with team members and stakeholders to align data infrastructure with platform goals and customer needs
• Participate in Sprint Planning, Standups, and related activities to drive data-focused initiatives forward
• Mentor and guide less experienced engineers, sharing expertise in data infrastructure and database optimization
• Support the team’s area of ownership by working with the Support organization to resolve customer-facing data issues
• Stay abreast of industry trends in data infrastructure and database technologies, incorporating relevant innovations into our systems
• Contribute to technical documentation, research publications, blog posts, and presentations at conferences and forums
• Innovation in AI: Enhance data infrastructure capabilities for an AI platform used by leading AI labs to develop powerful multi-modal large language models (LLMs)