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Description:
- Embed inside client environments to implement AI solutions for messy institutional data.
- Solve specific data problems using existing data from CRMs, warehouses, and document repositories.
Requirements:
- 4–8 years of hands-on data engineering experience with customer exposure in enterprise environments.
- SQL fluency and proficiency in Python; experience with AI agent workflows and understanding of LLM limitations.
Benefits:
- Competitive base salary and meaningful early-stage equity.
- Opportunity to shape product evolution and deployment playbooks in a foundational technical role.
Job title
Job type
Required experience
4 years
Salary
-
Degree requirement
No degree requiredLocation requirements
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Benefits
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