AI Engineer

• Design and build high-performance data ingestion and processing pipelines using frameworks such as Spark and Iceberg
• Implement workflows for data correlation, enrichment, and annotation
• Ensure data quality, lineage, and reproducibility across ingestion and transformation stages
• Support analytics and reporting through platforms such as Superset, Presto/Trino, and Spark SQL
• Design and maintain schemas for large-scale structured and semi-structured datasets
• Optimize storage strategies for performance and cost (SQL/NoSQL, MPP, object storage, distributed file systems)
• Apply indexing, partitioning, and tuning techniques for efficient big data analytics
• Integrate open-source models and embeddings into data workflows where applicable (e.g., RAG pipelines, FAISS)
• Build services that enable natural language querying and contextual enrichment of datasets
• Collaborate on fine-tuning pipelines to support security-driven use cases
• Ensure pipeline and storage solutions scale to handle high-volume data
• Implement monitoring, error handling, and resilience patterns in production
• Work with DevOps teams to containerize and deploy data services efficiently
• Translate requirements from product/security teams into robust data engineering solutions
• Contribute to PoCs, demos, and integration pilots
• Document solutions and participate in knowledge transfer with internal and partner teams

Data and AI Engineer – EMEA

Product Co-Founder – Competitive Intelligence AI Platform

Consulting AI Architect – Remote EU

AI Engineer