AI Data Engineer
@ Citadel Securities

New York, NY
$150,000
On Site
Full Time
Posted 1 day ago

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Job Details

Overview

The AI Data Engineer at Citadel Securities drives the strategic development and hands-on implementation of AI-powered tools and workflows to streamline operational processes and enhance decision-making.

Objectives

This role involves evaluating cutting-edge AI techniques, building and scaling agentic systems, and developing internal tools to automate repetitive tasks. You will prototype, translate prototypes into production-grade Python systems, and ensure robust operational excellence.

  • Develop and deploy AI solutions using modern frameworks
  • Collaborate with senior leaders and engineering teams
  • Automate operational processes and workflows
  • Build production-grade Python systems
  • Ensure high quality and robust AI output

Collaboration & Communication

Partner closely with non-technical finance teams and senior leaders to understand needs, frame AI use cases, and drive adoption through clear communication and demonstrations. Work with engineers to define security and data permissions practices.

Skills & Qualifications

A strong background in software engineering, AI, or data science with 4-8 years of experience is required. Proficiency in Python, production-grade code deployment, automation of processes, and expertise in NLP, LLMs, and modern AI stacks are essential.

  • 4-8 years of relevant experience
  • Expert-level proficiency in Python
  • Experience with production-grade AI systems
  • Strong foundation in NLP and LLMs
  • Capability to translate prototypes into scalable solutions

Key skills/competency

AI, Python, Data Engineering, Automation, NLP, LLM, Prototyping, Production Systems, Collaboration, Operational Excellence

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How to Get Hired at Citadel Securities

🎯 Tips for Getting Hired

  • Customize your resume: Highlight AI, Python and automation experience.
  • Research Citadel Securities: Understand their culture and mission.
  • Prepare technical portfolio: Showcase relevant AI projects.
  • Practice behavioral interviews: Emphasize problem-solving skills.

📝 Interview Preparation Advice

Technical Preparation

Review Python production code practices.
Study modern AI stacks and LLM platforms.
Practice building and deploying prototypes.
Familiarize with data-sensitive application security.

Behavioral Questions

Describe resolving ambiguous project challenges.
Explain collaboration with non-technical teams.
Discuss rapid prototyping experiences.
Share a time you adapted feedback quickly.

Frequently Asked Questions