Lead Software Engineer, Data Infrastructure & Analytics

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses. The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity. WHO WE ARE We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully. As Lead Software Engineer for Data Infrastructure and Analytics, you will design and scale the systems that power Serve’s robotics data platform. You’ll own the lifecycle of robot and cloud data, set technical direction, and mentor engineers to ensure our platform is a reliable foundation for analytics and operations. Your work will directly enable real-time robotics operations and analytics at scale. RESPONSIBILITIES - Technical Leadership & Roadmap: Define and own the technical roadmap for the data infrastructure platform, making key architectural decisions and ensuring alignment with company objectives. - Data Offload System: Own the development of our resilient data offload system, ensuring the fleet can meet strict SLAs and maximally utilize depots' available bandwidth. - Cloud Orchestration: Drive the creation of a centralized cloud service (Orchestrator) to manage bandwidth, prioritize data events, and coordinate offload activities across the entire fleet. - Analytics Pipeline: Build and maintain the infrastructure for ingesting and transforming robot metrics into queryable tables (e.g., BigQuery) and analytics-ready models using tools like dbt. - System Resiliency & Monitoring: Implement robust monitoring and ensure the entire system is resilient to interruptions, with features like automatic rollover and data integrity verification - Mentorship: Mentor other engineers on the team, fostering best practices in system design, coding, and operational excellence. QUALIFICATIONS - Experience & Background: 8+ years of professional software engineering experience, with at least 2 years in a technical leadership or lead engineer role. - Technical Skills: - Experience building large-scale distributed systems handling petabytes of data per day - Proficiency in at least one of Python, Go, or C++. - Proven experience building and operating large-scale, distributed data systems on a major cloud platform (GCP experience is preferred: GCS, BigQuery, Pub/Sub, Dataflow, etc.). - Deep understanding of data processing, ETL/ELT, networking principles, and I/O optimization. - Strong architectural skills, with the ability to design complex systems that are scalable, reliable, and maintainable. - Soft Skills: - Demonstrated ability to lead technical projects from conception to production. - Excellent mentorship skills and a passion for growing the capabilities of your team. - Strong communication skills and the ability to drive alignment across multiple teams. WHAT MAKES YOU STANDOUT - Experience in robotics, IoT, or a similar field involving data offload from fleets of edge devices. - Hands-on experience with data transformation and modeling tools like dbt. - Familiarity with containerization and orchestration technologies (Docker, Kubernetes). - Experience designing systems that must be resilient to network failures and other real-world interruptions.