Gen AI Analyst — LLMs, RAG & Deep Learning

Citi; New York (NY); Hybrid; USD 9,400 - 16,000; Full time

Job summary

Citi is seeking a Gen AI Analyst in its North America Data Science and Modeling group to develop generative AI solutions and ML models. You will work on training, evaluating, and deploying models, with emphasis on prompt engineering, RAG, and governance in a hybrid environment.

The role requires 1–3 years of hands-on AI/ML experience, strong Python/PySpark and SQL skills, and familiarity with large language models and related frameworks. Collaboration across teams is essential.

Qualifications

• 1-3 years of hands-on experience in an AI, ML, or data science role.
• Proficient in PySpark/Python/R and SQL.
• Experience with deep learning and generative AI.
• Familiarity with Transformers/LLMs and related tools.
• Strong communication and problem-solving skills.

Responsibilities

• Work with large and complex datasets to build Deep learning/generative AI solutions.
• Model training/fine-tuning, validation, deployment and governance.
• Design, fine-tune and implement LLMs/GenAI applications (prompt engineering, RAG, fine-tuning).
• Document data requirements, processing, cleaning, and exploratory analysis.
• Collaborate with team and business partners to deliver model-driven solutions.

Skills

PySpark

Python

R

SQL

Deep learning

Generative AI

Transformers/LLMs

Prompt engineering

RAG

Vector databases

Data warehouses

Statistical analysis

Education

Bachelor's / Master’s degree in Economics / Statistics / Mathematics / IT / Computer Applications / Engineering

Tools

TensorFlow

PyTorch

Hugging Face Transformers

LangChain

LlamaIndex

Job description

Citi is seeking a Gen AI Analyst in its North America Data Science and Modeling group to develop generative AI solutions and ML models. You will work on training, evaluating, and deploying models, with emphasis on prompt engineering, RAG, and governance in a hybrid environment.

The role requires 1–3 years of hands-on AI/ML experience, strong Python/PySpark and SQL skills, and familiarity with large language models and related frameworks. Collaboration across teams is essential.