Generative AI Data Engineer
Summary
Builds production-grade AI and data engineering solutions at Citi: designing governed data pipelines, integrating LLMs and RAG, and developing APIs, microservices, and agentic AI workflows using Python, SQL, and optionally Java for enterprise financial services.
Build scalable AI applications with Python, SQL, and agentic systems as a full-time AI Data Engineer at Citi. Apply hands-on software engineering in financial services.
This AI Data Engineer develops production-grade enterprise solutions supporting business processes and client delivery. You will create data pipelines, integrate machine learning models, and build APIs, microservices, and reusable AI components. The work includes LLMs, Retrieval-Augmented Generation, intelligent automation, and agentic workflows.
Key Responsibilities:
- Design intelligent agents covering perception, reasoning, planning, and execution
- Develop governed, secure data pipelines for AI workloads
- Integrate LLMs, reinforcement learning, and predictive models
- Build Python or Java applications, APIs, and microservices
- Document agent designs, implementations, and operational procedures
Requirements:
- Five-plus years of professional software development experience
- Two-plus years in AI/ML, Generative AI, or intelligent automation
- Strong Python and SQL proficiency; Java is a plus
- Experience with LLM applications, Prompt Engineering, and RAG
- Bachelor’s degree or equivalent experience
Bring software, data engineering, and Generative AI expertise to Citi’s scalable agentic technology solutions.