Offer summary

Qualifications:

Strong background in AI/ML development and strategic problem-solving., Experience with Azure and Snowflake for scalable AI architectures., Proficiency in developing predictive models and automation solutions., Familiarity with MLOps practices and tools like Apache Airflow..

Key responsabilities:

Identify high-value AI use cases and convert data into actionable insights.

Develop and deploy AI-driven solutions to optimize business processes.

Design and manage AI pipelines for efficient data processing and model deployment.

Collaborate with cross-functional teams to align AI initiatives with business goals.

Job description

About the Role

We are seeking a Senior AI Engineer who is technically skilled and highly creative in identifying AI opportunities across the company. You’ll play a key role in proactively exploring ways to leverage vast amounts of structured and unstructured data, building AI-driven solutions that drive business impact—whether in Fraud Detection, Sales Optimization, Operations Automation, or entirely new areas we haven’t thought of yet.

This role is ideal for someone who enjoys hands-on AI/ML development and strategic problem-solving, with a strong background in Azure, Snowflake, and scalable AI architectures.

Key Responsibilities

Proactively Identify AI Opportunities – Work closely with various teams to uncover high-value AI use cases and turn company-wide data into actionable insights.
Innovate with AI Solutions – Develop and deploy predictive models, automation solutions, and AI-powered tools that optimize business processes and decision-making.
Maximize Data Potential – Leverage the company’s large datasets to develop new AI-driven applications, from customer insights to operational efficiency improvements.
Scalable AI/ML Infrastructure – Design and manage end-to-end AI pipelines on Azure and Snowflake, ensuring efficient data processing and model deployment.
MLOps & AI Automation – Automate model lifecycle management with Azure Machine Learning, Apache Airflow, and CI/CD workflows for scalable AI operations.
Cross-functional collaboration – Partner with engineering, product, and business teams to align AI initiatives with company goals.
Stay Ahead of AI Trends – Keep up with the latest in AI/ML research, tools, and techniques to continuously improve company-wide AI capabilities.