DATA SCIENCE (Python + IA) - REMOTO ARGENTINA

Requisitos destacables:

* Experiencia en Python, LangChain y LangGraph.

* Experiencia reciente (no de hace mas de un año).

* Experiencia en desarrollo productivo, no solo trabajo con pruebas o prototipos.

Are you an experienced AI Engineer who has led the development of world-class software or digital products? Are

you looking for an opportunity to expand your scope and lead products used by some of the biggest and most

influential businesses around the world? If the answer to these questions is yes, we would like to talk with you.

Work you’ll do

We are seeking a highly skilled AI Implementation Specialist to join our agile team focused on developing a

multi-agent AI solution. This solution will consist of three primary agents: one to understand large data sets,

another to recommend strategic functional modifications to data experiments and existing modeling configurations

for better outcomes based on correct contextual interpretation of the large data sets, and a third to ultimately

construct an execution agent to run perturbed models or variants based on the recommendations. The successful

candidate will work closely with a team of six+ professionals, leveraging their expertise in Python, LangChain, and

large language models (LLMs) to interpret and analyze data frames and structured data (SQL, CSV, Parquet).

Key Responsibilities:

● Collaborate with a cross-functional agile team to design, develop, and implement a multi-agent AI

solution.

● Utilize Python, LangChain, and LangGraph to build and integrate AI models capable of interpreting data

frames and structured data.

● Work with large language models (LLMs) to process and analyze data from SQL databases and CSV or

Parquet files.

● Ensure the AI agents interpret existing data sets, outputs from modeled data, and curated third-party data

sets to derive domain-specific insights.

● Develop the AI agents to match the skills and responses of functional experts, serving as the reference

benchmark for data interpretation and exploration.

● Participate in daily stand-ups, sprint planning, and retrospective meetings to ensure project milestones are

met.

● Contribute to the continuous improvement of the development process and the overall quality of the AI

implementation.

● Document technical specifications, development processes, and project progress.