Span

About the Company

Span is the AI-native developer intelligence platform that helps software engineering leaders cut coordination costs and drive performance at scale. Span brings clarity to engineering organizations with a holistic, human-centered approach to developer productivity. World-class companies like Ramp, Vanta, Carvana, Writer, and Braze use Span to get a complete picture of engineering impact and health, drive high performance, and make smarter business decisions. We recently launched an AI Code Detector. It's powered by span-detect-1, a state-of-the-art machine learning model for chunk-level detection of AI generated code at 95% accuracy. The model ties AI coding assistants to code shipped into production for the first time, creating clearer visibility into adoption, impact, and ROI. Span is backed by Alt Capital, Craft Ventures, SV Angel, Bling, BoxGroup, and dozens of founders, CTOs and CPOs at places like Slack, Notion, Rippling, and Square.

Listed Jobs

Company Name

Span

Job Title

Backend Engineer

Job Description

**Job Title** Backend Engineer **Role Summary** Design, develop, and maintain scalable backend services for a software engineering intelligence platform. Core tasks include building data connectors, modeling unified data schemas, converting pipelines to incremental workloads, and implementing AI‑agent backends that interface with knowledge graphs and large language models (LLMs). **Expectations** * Deliver high‑performance, production‑grade services that support front‑end and AI features. * Efficiently manage cost and uptime in cloud environments. * Work closely with full‑stack engineers to expose clean APIs and data services. * Continuously refactor and optimize data pipelines and models for scalability. **Key Responsibilities** 1. Build and maintain connectors for integration platforms (e.g., BitBucket, Shortcut). 2. Design and implement unified data models for new data domains such as incident and monitoring systems. 3. Refactor existing ETL pipelines into incremental workloads and event‑driven architectures. 4. Develop AI‑agent backends that allow LLMs to query knowledge graphs and generate insights. 5. Optimize database schemas, caching strategies, and message queues for performance and cost. 6. Deploy and manage services in cloud environments using container orchestration and CI/CD tools. **Required Skills** * Backend development: TypeScript (NestJS), Python, or equivalent. * Data integration: Airbyte, Dagster, Kafka, ETL, data modeling, incremental processing. * Databases: Postgres, Redis. * Cloud & DevOps: AWS, Kubernetes (K8s), Docker, FluxCD, CI/CD pipelines. * LLM integration: experience with prompt engineering, LLM APIs, and knowledge graph interaction. * Performance tuning, scalability, and reliability practices in distributed systems. * Strong problem‑solving and communication skills. **Required Education & Certifications** Bachelor’s degree in Computer Science, Software Engineering, or related field, OR equivalent practical experience. No specific certifications required.

San francisco, United states

Hybrid

28-11-2025