Build, operate, and enhance data infrastructure for Agentic AI initiatives, collaborating with ML engineers, AI scientists, and product managers
Job Summary
Build, operate, and enhance data infrastructure for Agentic AI initiatives, collaborating with ML engineers, AI scientists, and product managers.
Design, develop, and maintain scalable data pipelines and ETL/ELT processes, ensuring compliance, auditability, and protection of sensitive information.
Contribute to production-ready, secure, and compliant data solutions while growing toward 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, AI scientists, and product managers.
Skills & Requirements
Must-have
Scalable data pipelines and ETL/ELT
Python programming proficiency
Strong SQL skills
Cloud platform experience (AWS, Azure, or GCP)
Data governance and security controls
Automated data validation and testing
Nice-to-have
Vector embedding stores and knowledge graphs
RAG data pipelines and LLM fine-tuning
Infrastructure-as-code and automated deployment
Containerization and orchestration tools
Key Requirements
3+ years of professional experience in data engineering
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field
Working experience with Java or Scala
Familiarity with data warehousing and lakehouse platforms
Experience with orchestration frameworks and CI/CD practices