AI Engineer

Parser

AI Engineer focusing on building and operating AI-driven solutions in production for a fast-growing organization. Collaborating within a multicultural community and optimizing for user value.

Posted 5/17/2026full-timeMadrid • 🇪🇸 SpainMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

SparkSQL

About the role

Key responsibilities & impact

Build, deploy, and operate AI-driven solutions in production.
Collaborate openly within the team.
Communicate decisions, assumptions, and trade-offs clearly to the team.
Experiment, validate quickly, and iterate based on frequent stakeholder and team feedback.
Optimize for Analytics and Trading adoption, clarity, and trust.
Make sensible trade-offs to deliver usable value early.
Adapt as the team and project scale in communication, scope, and technical direction.

Requirements

What you’ll need

Demonstrated +5 years of experience in data engineering and AI/system development in a production environment.
Proven ability to ship iterative, user-focused solutions with attention to reliability and safety.
Strong communication skills and a collaborative mindset.
Strong SQL and experience working with large analytical datasets.
Familiarity with distributed data platforms (e.g., Spark, Trino, Databricks).
Understanding of data modelling, joins, aggregations, and performance trade-offs.
Experience operationalizing ML and LLM-based systems in production environments.
Familiarity with model lifecycle management (training, versioning, deployment, rollback).
Understanding of AI evaluation approaches (offline tests, benchmarks, qualitative review).

Benefits

Comp & perks

A highly competitive compensation package.
Medical insurance.
The chance to join an organization with triple digit growth that is changing the paradigm on how software products are built.
The opportunity to form part of an amazing, multicultural community of tech experts.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringAI developmentsystem developmentSQLdata modellingjoinsaggregationsoperationalizing MLLLM-based systemsmodel lifecycle management

Soft Skills

communication skillscollaborative mindsetability to ship iterative solutionsattention to reliabilityattention to safetyadaptabilitydecision-makingassumption communicationtrade-off analysisstakeholder feedback incorporation