Build, operate, and enhance data infrastructure supporting Agentic AI initiatives, collaborating with ML engineers, AI scientists, and product managers
Job Summary
Build, operate, and enhance data infrastructure supporting Agentic AI initiatives, collaborating with ML engineers, AI scientists, and product managers.
Design, develop, and maintain scalable data pipelines and ETL/ELT processes, applying data governance and security controls for AI research, prototyping, and production use cases.
Contribute to production-ready, secure, and compliant data solutions within the R&DS AI Innovation Program, growing towards deeper architectural ownership.
Matching Summary
Build, operate, and enhance data infrastructure supporting Agentic AI initiatives, collaborating with ML engineers, AI scientists, and product managers.
Skills & Requirements
Must-have
Scalable data pipelines and ETL/ELT
Data governance and security controls
Automated data validation and testing
Python programming proficiency
Strong SQL and NoSQL experience
Cloud platform experience (AWS, Azure, GCP)
Orchestration frameworks and CI/CD
Nice-to-have
Agentic AI initiative support
Near real-time agent interactions
Vector embedding stores and knowledge graphs
Data quality for ML/LLM pipelines
Infrastructure-as-code deployment
Containerization and orchestration tools
Key Requirements
3+ years of professional data engineering experience
Bachelor's or Master's degree in Computer Science or related field