Lead AI Engineer, Banking Tech (Hybrid)

Citi; Jersey City (NJ); Hybrid; USD 177,000 - 265,000; Full time

Job summary

Citi in Jersey City, NJ, is seeking a hands-on Applied AI Lead Engineer in Banking Technology SVP for a hybrid work arrangement. You will architect, build, and deploy agentic AI solutions and scalable AI frameworks for core banking use cases.

You will integrate ML/LLM tools into full‑stack apps, drive MVPs with rapid iterations, define evaluation metrics, and collaborate with researchers, data scientists, product managers, and engineers to deliver production‑ready AI capabilities.

Qualifications

• Bachelor’s degree or equivalent; Master’s preferred.
• 10+ years of progressive software engineering with hands-on coding, producing AI features.
• 3+ years dedicated to AI, prompt engineering, ML, Generative and/or agentic AI systems.
• Experience architecting enterprise-scale AI projects.

Responsibilities

• Lead end-to-end design, hands-on implementation, and deployment of scalable agentic AI frameworks and generative AI solutions for banking use cases.
• Build full-stack applications that integrate ML/LLM tools into AI solutions.
• Champion MVP-first approach with rapid iterations, A/B testing, and value delivery.
• Design metrics and evaluation strategies for AI system performance and behavioral improvement.

Skills

Python/Java

UI frameworks

Databases

AI/ML concepts

LLMs integration

APIs design

Docker/Kubernetes

CI/CD

Agile methods

Banking domain knowledge

Education

Bachelor's degree

Master's degree preferred

Tools

LanGraph

LangChain

AutoGen

CrewAI

N8N

TensorFlow

PyTorch

Scikit-Learn

NumPy

Pandas

Git

Job description

Citi in Jersey City, NJ, is seeking a hands-on Applied AI Lead Engineer in Banking Technology SVP for a hybrid work arrangement. You will architect, build, and deploy agentic AI solutions and scalable AI frameworks for core banking use cases.

You will integrate ML/LLM tools into full‑stack apps, drive MVPs with rapid iterations, define evaluation metrics, and collaborate with researchers, data scientists, product managers, and engineers to deliver production‑ready AI capabilities.