Senior AI & Agentic Engineer – Expression of Interest (Future Opportunities)

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Expression of Interest – Future Opportunities

We’re building a pipeline of talented professionals interested in future opportunities with Artefact. This posting is for resume collection and does not represent an immediate vacancy. We welcome you to share your resume, and our recruiting team may reach out as opportunities aligned with your experience become available.

Who We Are

Founded and headquartered in Paris, Artefact is a next-generation consulting firm, specializing in data, analytics & AI consulting, dedicated to transforming data into business impact across the entire value chain of organizations. We are proud to say that we help our clients grow their data and digital capabilities, and that we’re also growing in parallel.

We have 2000 employees across 36 offices who are focused on accelerating digital transformation. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts are all dedicated to bringing extra value to every client. We design data-based solutions to meet our clients' specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we've acquired with our 1000+ client base around the globe.

Find out more at artefact.com.

Our Opportunity

We are looking for a Senior AI & Agentic Engineer to join our dynamic team. This role is ideal for someone with a deep understanding of data engineering and a proven track record of leading data projects in a fast-paced environment.

Key Responsibilities

• Design, build, and maintain scalable and robust data pipelines using SQL, Python, Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow and Pyspark.

• Lead the integration of complex data systems and ensure consistency and accuracy of data across multiple platforms.

• Implement continuous integration and continuous deployment (CI/CD) practices for data pipelines to improve efficiency and quality of data processing.