Streamlining operational processes and enabling faster, more scalable decision-making across Citadel Securities through AI-powered tools and agentic workflows
Requirements
- Expert-level proficiency in Python and experience deploying production-grade code (not just notebooks)
- Demonstrated experience automating operational processes, deploying LLM-based tools to production, or building agentic workflows
- Strong working knowledge of NLP, LLMs, and modern AI stacks
- Experience in full-stack prototyping and rapid development frameworks like Streamlit, Flask, or similar
- Familiarity with data infrastructure, permissions design, or integration of AI into existing software systems
- 4-8 years of hands-on experience in software engineering, AI engineering, or data science (with strong engineering fluency)
- Proven ability to scope ambiguous problems, develop end-to-end solutions, and communicate outcomes effectively
Responsibilities
- Keep up to date with and evaluate cutting edge AI techniques and architectures that can enhance or replace existing operational workflows
- Build, test, and scale agentic systems using modern frameworks
- Develop internal tools and full-stack applications to automate repetitive or high-effort tasks across departments
- Translate prototypes into production-grade Python systems, with an emphasis on maintainability and performance
- Ensure AI-generated outputs are reviewed and verified; build tools and guardrails to mitigate hallucinations and quality risks
- Design experiments, iterate quickly, and deliver working solutions in fast-moving, ambiguous environments
- Partner with senior leaders and non-technical finance teams to understand needs, frame AI use cases, and drive adoption through accessible communication and demonstrations
Other
- 4-8 years of hands-on experience in software engineering, AI engineering, or data science (with strong engineering fluency)
- Strong collaboration and communication skills; capable of simplifying complex topics for non-technical colleagues
- A passion for staying current with AI trends and bringing novel techniques into practical use
- An experimental mindset: comfortable testing hypotheses, learning from failures, and iterating quickly; doesn’t shy away from problems with no right answer
- Opportunities may be available from time to time in any location in which the business is based for suitable candidates
