AI Engineer (Cloud/Data)

TL;DR

AI Engineer (Cloud/Data): Designing and scaling AI/ML solutions within cloud-native environments with an accent on data pipeline orchestration and model deployment. Focus on building intelligent systems for commerce transformation, predictive analytics, and real-time decisioning using GCP, Azure, and AWS.

Location: Must be based in Colombia (Remote)

Company

hirify.global is a global experience innovation company that leverages data, AI, and technology to help brands achieve digital transformation.

What you will do

• Design and scale AI/ML solutions across GCP, Azure, and AWS for anomaly detection and predictive KPIs.
• Develop unified data pipelines and orchestrate model training workflows using Databricks.
• Collaborate with cross-functional teams to operationalize models that drive measurable business impact.
• Build AI-powered dashboards and explainable insights using tools like Power BI, Tableau, or Looker.
• Implement performance monitoring, drift detection, and feedback loops for deployed models.
• Support conversational analytics and GenAI interfaces for marketing and commerce data querying.

Requirements

• 5+ years of experience building and deploying machine learning models in production.
• Proficiency with Databricks and cloud-native ML tooling (GCP Vertex AI, Azure ML, or AWS SageMaker).
• Strong programming skills in Python and SQL.
• Experience with frameworks such as scikit-learn, TensorFlow, PyTorch, or MLflow.
• Proven ability to build data pipelines and model-serving systems in enterprise environments.
• Experience creating AI-integrated dashboards using Power BI, Tableau, or Looker.

Nice to have

• Experience with orchestration tools like Airflow or event-based workflows (Kafka, Pub/Sub).
• Knowledge of MLOps best practices including drift detection and version control.
• Experience with LLM/GenAI for insights extraction and conversational UX.
• Background in retail or multi-brand global ecosystems.

Culture & Benefits

• Opportunity to work on global-scale projects for well-known organizations.
• Commitment to an equitable and inclusive workplace.
• Focus on continuous learning and professional growth.
• Supportive environment for career development and impact.

Hiring process

• Initial screening by the Talent Acquisition team.
• Technical and cultural fit interviews.