Senior Data Engineer – AI/LLM Training (Remote)

Kake; Argentina; Presencial; ARS 1.800.000 - 3.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote-first

Competitive pay in USD

Fully remote

Personal growth fund

Social impact community

Descripción de la vacante

Kake is seeking a Senior Data Engineer to help develop and evaluate AI training data for a leading human data platform powering AI agents and LLMs. You will operate at the intersection of software engineering and artificial intelligence, writing prompts, delivering reference-quality code, evaluating model outputs, and shaping how code is understood by next-generation models.

The role emphasizes building end-to-end data pipelines, running tests, managing environments, and contributing to robust

Formación

• 5+ years of professional software engineering experience.

Responsabilidades

• Contribute to the development and evaluation of AI training data for AI agents and LLMs.
• Write prompts for AI training and evaluation.
• Produce reference-quality code solutions.
• Provide structured human signal to improve AI systems.
• Evaluate AI agent performance on terminal-based tasks.
• Work with tasks including compiling code, running tests, managing environments, and completing multi-step software engineering workflows.
• Write functional and integration tests.
• Help ensure the quality of AI-generated software engineering outputs.

Conocimientos

Python

Node.js

TypeScript

Rust

Go

Linux

Docker

Git

Testing

PostgreSQL/SQL

Herramientas

PostgreSQL

SQL

Descripción del empleo

Kake is seeking a Senior Data Engineer to help develop and evaluate AI training data for a leading human data platform powering AI agents and LLMs. You will operate at the intersection of software engineering and artificial intelligence, writing prompts, delivering reference-quality code, evaluating model outputs, and shaping how code is understood by next-generation models.

The role emphasizes building end-to-end data pipelines, running tests, managing environments, and contributing to robust