Role Overview
The Algorithmic Trading Quant team is part of Citi Global Markets and is responsible for the research, design, implementation, and maintenance of Equities Execution Algorithms and related Trading Products offered to Citi’s institutional clients and internal trading desks. The team collaborates with global teams, with a specific focus on North America and LATAM markets.
Development Value
The Algorithmic Trading Quant team is seeking a highly skilled and motivated Senior Rust Engineer to join our NAM Equities Cash Quant team. This is a unique opportunity to work at the intersection of quantitative finance, lead the design and development of next-generation ultra-low-latency trading systems, and leverage an AI-assisted software development lifecycle with Large Language Models (LLMs). It represents an exciting opportunity to be involved in high-impact initiatives, pioneer modern systems programming in the Electronic Trading domain, and drive the expansion of Citi’s Equity Trading franchise.
Responsibilities
- Design, develop, benchmark, and optimize next-generation, ultra-low-latency equity trading platforms and algorithmic execution engines using Rust (and existing low-latency Java/C++ stacks where applicable).
- Work closely with quantitative researchers and business stakeholders to translate complex financial models, pricing signals, and execution strategies into robust, scalable, and deterministic production software.
- Drive the adoption and integration of AI and Large Language Models (LLMs) into the software development lifecycle, exploring applications for automated code generation, intelligent debugging, performance profiling, and automated testing.
- Collaborate on researching and analyzing enhancements to existing algorithms (e.g., liquidity seeking, Smart Order Routing) and developing new models (e.g., market impact models) and short-term predictive signals (e.g., fair value calculation).
- Perform analysis and processing of high-throughput market data, order books, execution logs, and derived real-time analytics.
- Enhance the model development, backtesting, and high-fidelity market simulation frameworks.
- Work in close partnership with the Coverage desk, Technology teams, and control functions (Legal, Compliance, Risk, and Audit) to ensure robust risk management, governance, and control infrastructure.
- Build a culture of responsible finance, sound governance, supervision, expense discipline, and ethics.
- Adhere to Citi’s Code of Conduct and the Plan of Supervision for Global Markets and Securities Services; ensure team-wide compliance.
- Obtain and maintain all required regulatory registrations and licenses within the designated timeframe.
- Appropriately assess risk when business decisions are made, demonstrating consideration for the firm's reputation and safeguarding Citigroup, its clients, and assets.
Knowledge & Experience
- Extensive experience (3+ years) in systems programming, with strong proficiency in Rust (or low-latency C++/Java with substantial production Rust experience), focusing on concurrency, cache-friendly data structures, zero-cost abstractions, and low-latency / lock-free design.
- Practical experience with Rust memory management, lifetimes, ownership semantics, unsafe code audits, and asynchronous runtimes (e.g., Tokio) or bare-metal event loops.
- Strong background in high-performance networking, kernel-bypass technologies, IPC, and custom binary protocols (e.g., FIX, ITCH, OUCH, SBE) is a significant advantage.
- Experience working in a development environment with an AI-integrated software development lifecycle is highly preferred.
- Deep understanding of algorithms, systems architecture, OS-level profiling, and performance tuning (e.g., perf, flamegraphs, memory layout optimization).
- Minimum of 3 years of experience in a financial trading environment preferred, particularly in research and development of agency execution algorithms, smart order routing (SOR), liquidity seeking, market making, or high-frequency trading (HFT) strategies.
- Strong understanding of US Equity algorithmic trading mechanics and market microstructure.
- Experience with statistical modeling, machine learning, and time-series analytics (e.g., Q/KDB+, Polars, or specialized time-series databases) is desirable.
- Strong verbal and written communication skills with the ability to collaborate effectively across quantitative research and trading desks.
- Ability to manage multiple projects simultaneously in a fast-paced front-office environment.
Qualifications
- Education: Master's or PhD in Computer Science, Engineering, Mathematics, Finance, or a related quantitative field. Exceptional candidates with a Bachelor's degree and proven track record in low-latency systems development will be considered.
- Applicable Licenses: Required to already hold or obtain upon arrival FINRA Series 7, 57, and 63 registrations.
