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Span is looking to fill a Product Engineer position based primarily in Argentina. Read below for more information.
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.
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.
We’re looking for someone who can help with these types of example projects:
A product that root causes KTLO work and recommends solutions.
A software catalog that works for monoliths and that people actually want to use.
Help protect engineering focus time by systemically solving sources of distraction or mental load with AI.
What we're looking for:
Resourceful individuals who thrive in a high agency environment.
Have been a founder, seed-stage engineering hire, or have launched your own project before.
You have strong product sense and can prove it.
Have experience working with LLMs and agentic workflows.
About our Stack:
TypeScript, NestJS, React, Postgres, Redis
Airbyte, Dagster, Python, Kafka
AWS, K8S, FluxCD
Interview process
Silver Screening Interview.
Silver Technical Interview.
Client Screening Interview.
Client Technical Interview.
Client Behavioral Interview.
After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.
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