Lead the development and optimization of data infrastructure supporting Agentic AI initiatives.
Collaborate with ML engineers, AI scientists, and product managers to architect, implement, and maintain robust data pipelines.
Design, develop, and maintain scalable data pipelines and ETL processes supporting AI research and development.
Monitor and troubleshoot data pipeline issues to ensure continuity and reliability.
Drive data platform reliability, scalability, and cost optimization across cloud-based infrastructure.

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field; advanced degree preferred.
5+ years of professional experience in data engineering, including at least 2 years focused on ML/AI data infrastructure.
Advanced proficiency in Python and Scala; experience with Rust, Go, Java, or Julia is valued.
Expert-level knowledge of SQL and NoSQL databases.
Hands-on experience with vector databases (e.g., Pinecone, Weaviate, Milvus).
Proficiency with modern data orchestration platforms (e.g., Airflow 2.x).
Extensive experience with at least one major cloud platform (AWS, Azure, or GCP).
Expertise in containerization and orchestration (Docker, Kubernetes).
Experience with Infrastructure as Code tooling (e.g., Terraform).
Experience with distributed computing frameworks (Spark, Dask, Ray).
Proficiency with streaming technologies (Kafka, Flink).
Knowledge of modern data lakehouse architectures.
Certifications in cloud platforms, big data technologies, engineering, or ML operations preferred.

Senior AI Data Engineer

Key skills