LLM Engineer for AI-Driven FinTech Production

Cantor Fitzgerald; New York (NY); On-site; USD 140,000 - 160,000; Full time

Job summary

Cantor Fitzgerald Technology Markets LLC is seeking a Machine Learning Engineer to build AI-driven, production-ready LLM applications for a high‑volume financial services environment. You will collaborate with product, engineering, and business teams to design, test, and operationalize innovative AI features.

You will develop data pipelines, write clean Python code, and implement guardrails for responsible AI, latency, cost control, and monitoring across services.

Qualifications

• Bachelor’s degree in CS/ML or related field.
• Experience delivering production-ready software in Python.
• Hands-on with LLM tools, prompts, and retrieval workflows.
• Experience with data pipelines and monitoring.

Responsibilities

• Design and implement LLM-driven features in production systems.
• Build and maintain data pipelines for both structured and unstructured data.
• Write clean, testable Python code and maintain reusable libraries.
• Develop prompts, tool‑calling workflows, and retrieval pipelines.
• Create evaluation suites, define success metrics, and analyze failures.
• Diagnose and mitigate hallucination, latency, and cost issues.
• Collaborate with product, engineering, and business stakeholders.
• Implement monitoring, logging, and alerting for AI services.
• Contribute to responsible‑AI guardrails and human‑in‑the‑loop processes.
• Document designs, experiments, and findings for internal knowledge sharing.

Skills

Python

LLM tooling

Data pipelines

Prompts & retrieval

Testing & monitoring

Cloud & containers

Education

Bachelor's degree in CS/ML or related

Tools

LLM frameworks

Cloud platforms

Containers

Job description

Cantor Fitzgerald Technology Markets LLC is seeking a Machine Learning Engineer to build AI-driven, production-ready LLM applications for a high‑volume financial services environment. You will collaborate with product, engineering, and business teams to design, test, and operationalize innovative AI features.

You will develop data pipelines, write clean Python code, and implement guardrails for responsible AI, latency, cost control, and monitoring across services.