Role overview

Span is looking to fill a Backend Engineer position based primarily in Argentina. Read below for more information.

Our Vision

Why do engineering organizations slow down as they get bigger? Building software is fundamentally a context problem that scales poorly. The knowledge needed to build the right thing, in the right way, is fragmented across people and systems. This fragmentation isn’t just frustrating - it fundamentally limits how engineering organizations operate.

Span chose to start by solving the context problem for engineering leaders to enhance developer productivity. However, the lack of context that hinders CTOs from fully understanding their organization also impacts developers and, critically, is a major bottleneck for AI agents.

We are creating a new type of tool that delivers coherent and useful software engineering context for humans and agents alike, a tool that we believe will enable ownership, autonomy, and superhuman impact inside of an engineering organization.

About Span

We are a Series A stage startup backed by Alt Capital, Craft Ventures, SV Angel, Box Group, and dozens of founders from companies such as Slack, Rippling, and Notion. Customers include leading engineering organizations such as Ramp, Vanta, and Carvana. Today, we primarily compete in the Software Engineering Intelligence Platform vertical but we will increasingly compete with Internal Developer Portals, and AI Powered Devtools. Our entire engineering team can currently be fed with four pizzas.

Role details

We’re looking for someone who can help with these types of example projects:

Developing a connector for a new integration, such as BitBucket or Shortcut.
Design and implement a unified data model for a new category of data relevant to the Software Engineering Intelligence space, such as incident management systems or monitoring systems.
Convert data pipelines to incremental workloads to improve performance, build out event based data processing framework that scales.
Create an AI Agent workflow backend that provides tools for LLMs to query a knowledge graph to produce reports and insights for our customers.

You

Have built products with a backend or data lean, ensuring the app is prepared to scale, solving all kinds of bottlenecks and enabling Full-Stack and Front-End engineers to create delightful UI experiences.
Have experience working with data pipelines and ETL processes, data modeling and optimization techniques, and high-performance data reads from external API sources.
Have spinned up your own projects in a cloud environment before, ensuring uptime and budget constraints are met.
Have experience integrating Large Language Models (LLMs) and understanding of prompt engineering in personal or professional projects.
Have a passion for technology, innovation, and learning and you can prove it.

Interview process

Silver Screening Interview.
Silver Technical Interview.
Client Screening Interview.
Client Technical Interview.
Client Behavioral Interview.

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