Senior Backend Engineer

SENIOR BACKEND ENGINEER Overview We are seeking a Senior Backend Engineer to own the core data infrastructure powering an AI-driven logistics platform. This is a high-ownership, zero-to-one role where you will design and scale systems that ingest, process, and serve real-time logistics data across AI pipelines, queues, databases, and search layers. You will set technical direction for the backend, operate with significant autonomy, and have an outsized impact on product reliability and performance from day one. What You'll Do Architect and scale distributed backend systems, design queue pipelines, communication hubs, and observability layers, and build for failure with retry strategies, circuit breakers, and graceful degradation Own database design and reliability, schema design, indexing, query optimization, and data pipelines that keep systems in sync at scale Build an AI search infrastructure for real-time logistics lookup and AI-driven features Define service boundaries and set engineering standards for the backend Collaborate directly with founders on roadmap and technical direction Help hire and mentor future backend engineers as the team scales Requirements — Must Have 5 years of professional backend software engineering experience Meaningful time in a high-growth startup or high‑scale production environment Demonstrated ability to own and ship backend systems end-to-end in fast-moving, ambiguous environments Track record of making sound architectural trade-offs under time pressure and revisiting decisions as requirements evolve Strong opinions about backend systems, held loosely, defended with clarity Real startup experience (10+ person company), not just big tech Self‑starter who prefers being handed a problem over a set of tickets and owning the outcome, not just the code Based in SF or committed to relocating (in-person, non‑negotiable) H-1B transfer OK, OPT OK, No new sponsorship Requirements — Nice to Have Experience with distributed systems, message queues (Kafka, RabbitMQ, SQS), and event-driven architectures Familiarity with AI/ML pipeline infrastructure or document processing at scale Exposure to enterprise software requirements — security, data retention, privacy, compliance Experience with search infrastructure (Elasticsearch, pgvector) Background at a high-growth Series A/B startup or as a founding engineer Logistics, customs, or regulated industry software experience Top 50 university background (soft preference, strong track record always wins) Success Metrics System reliability: Core services and queue-driven workflows maintain high uptime and low error rates under production load Throughput & latency: Message processing pipelines and search queries meet defined SLAs as data volumes grow Architectural quality: Backend systems are extensible, well-documented, and enable other engineers to build confidently Velocity: Scope, build, and ship new backend capabilities within sprint cycles without sacrificing correctness or resilience Autonomy: Resolve complex technical blockers independently and surface the right issues at the right time #J-18808-Ljbffr