TL;DR

Field Engineer (AI): Acting as a technical partner to build and execute complex technical solutions and automations for AI models with an accent on enterprise integrations, data quality, and operational efficiency. Focus on designing programmatic quality checks, developing automation workflows, and optimizing data exchange for AI-driven projects.

Location: Remote (Argentina / Mexico)

Company

%hirify_global% (Welo Data) partners with technology companies, leveraging over 25 years of experience and a global community of AI training and domain experts to provide high-quality datasets for AI models.

What you will do

Serve as a technical bridge and advisor between quality, operations, sales, and engineering teams.
Troubleshoot and optimize enterprise integrations to ensure seamless data exchange.
Plan and execute complex technical solutions that support customer and internal team success.
Consult with customers and internal teams on best practices for platform use, automation, and data quality.
Create self-serve solutions that empower internal teams to handle common technical tasks independently.
Design and implement programmatic quality checks to improve data consistency and accuracy.

Requirements

2+ years of engineering experience, ideally in a client-facing setting.
Bachelor's degree with an engineering or analytics focused field (e.g., Computer Science, Engineering, Mathematics, Statistics) or equivalent work experience.
Hands-on experience in ML lifecycle applications, data management, and data wrangling.
Technical experience in Python, JavaScript, or another relevant language for automations, integrations, and scripting.
Experience working with APIs, data pipelines, and automation frameworks.
Customer success mindset, with a passion for helping internal teams and customers succeed.

Nice to have

Experience with cloud platforms (AWS, GCP, or Azure) and data processing tools.
Python experience with C#.
Understanding of NLP concepts and techniques.
Passion for AI and ML technologies.

Culture & Benefits

Collaborative team environment focused on continuous learning and adaptation to new technologies.