Build, operate, and enhance data infrastructure for Agentic AI initiatives, collaborating with ML engineers and AI scientists
Job Summary
Build, operate, and enhance data infrastructure for Agentic AI initiatives, collaborating with ML engineers and AI scientists.
Design and maintain scalable data pipelines, ETL/ELT processes, and efficient data models to support AI research, prototyping, and production use cases.
Contribute to production-ready, secure, and compliant data solutions while growing towards deeper architectural ownership within the R&DS AI Innovation Program.
Matching Summary
Build, operate, and enhance data infrastructure for Agentic AI initiatives, collaborating with ML engineers and AI scientists.
Skills & Requirements
Must-have
Data pipelines and ETL/ELT
Data governance and security
Data models for analytics and ML
Automated data validation and testing
Python and SQL proficiency
Cloud platform experience (AWS, Azure, GCP)
Nice-to-have
Vector embedding stores and knowledge graphs
RAG data pipelines and LLM fine-tuning
Streaming or event-driven data processing
Infrastructure-as-code and automated deployment
Key Requirements
3+ years of professional data engineering experience
Bachelor’s or Master’s degree in Computer Science or related field