AI Engineer

We are seeking a AI Engineer to join our Data Department. In this role, you will be at the core of our mission to transform data into intelligent, automated, and predictive capabilities, ensuring that our business teams can make smarter, faster, and more impactful decisions.
As an AI Engineer, you will be responsible for designing, building AI solutions that serve internal stakeholders across BI, Sales, Operations, Finance, and Marketing.
You will focus on embedding AI models and automation into our data ecosystemparticularly within our Looker BI platformto enhance decision intelligence, operational efficiency, and business performance.
This role requires a strong mix of machine learning expertise, data engineering knowledge, and cross-functional collaboration. You will partner closely with data engineers, BI developers, and data product managers to translate business requirements into reliable, production-ready AI applications that deliver measurable impact across.
If you are passionate about building applied AI systems that transform how teams use data to make decisions in a global, data-driven environment, this opportunity is for you.
What will you do?
As an AI Engineer, you will design, deliver, and scale AI-driven solutions that power our data products and insights.
You will partner with engineers, analysts, and business stakeholders to develop machine learning models and data pipelines that bring automation and intelligence to the heart of our operations.
Your responsibilities will include:
Identify high-impact opportunities for automation, forecasting, and optimization using advanced ML and generative AI techniques.
Ensure AI models follow our governance and quality standards, focusing on scalability, explainability, and sustainability.
Model Development & Delivery
Collaborate with data engineers to ensure robust data flows and architecture in BigQuery and other cloud-based environments.
Integrate AI outputs from semantic layers and analytics tools to democratize access to intelligent insights.
Measure and track model performance, gather stakeholder feedback, and iterate to drive continuous improvement.
Promote responsible AI adoption across data teams by providing guidance, training, and documentation.
Contribute to a culture of data innovation and collaboration within the Data Department.