Back in 2012, we were a group of engineers and designers who decided we wanted to build things—so we did.
Able started as an engineering and product hub building for a portfolio of early-stage startups.
We built many relationships while developing products that were thoughtful, effective, and genuinely useful.
But, since then, we’ve grown… and so has our ambition.
Now, we’re entering our next chapter—defined by applied AI.
AI is a powerful force in the end-to-end software development cycle, and we’re creating practices that allow us to deliver software fast and more effectively than traditional approaches, creating meaningful value for our partners.
Today, our builder mindset is driving us to become an AI-native organization across every function.
We’re still evolving, and that’s part of the opportunity.
If you want to build, learn, and tackle challenges alongside an ambitious team, let’s build together.
This position is 100% remote within LatAm.
What you’ll be doing We are seeking someone who views the Knowledge Graph not just as a database, but as a living organism that requires constant care, feeding, and pruning.
You understand that a RAG system is only as good as the data underlying it.
You are intrigued by the complexity of ingesting massive, messy datasets and transforming them into clean, connected knowledge.
In short, someone who likes: Architecting Graph ETL: Designing and developing robust ETL pipelines specifically for graph ingestion.
You aren't just dumping rows into tables; you are determining how disparate data sources connect, evolve, and relate in a graph structure.
Data Ingestion at Scale: Managing high-volume data streams using tools like Kafka and implementing CDC (Change Data Capture) patterns to ensure the graph reflects real-time reality.
Automated Graph Hygiene: Writing scripts and jobs for deduplication, orphan node detection, and data consistency checks.
You take pride in a clean schema.
Modeling Time: Handling complex temporal relation.