Quantitative Developer, Systematic Equities

Overview

Quantitative Developer, Systematic Equities. Millennium is a top tier global hedge fund with a strong commitment to leveraging market innovations in technology and data to deliver high-quality returns.

Job Description

We are seeking a highly skilled and entrepreneurial Lead Software Engineer to architect, build, and scale the core trading infrastructure for a newly formed quantitative trading pod. You will lead the design and deployment of systems that support systematic strategies operating across global markets and time zones. This is a hands-on leadership role at the intersection of technology, research, and trading - you ll collaborate directly with quantitative researchers and the Senior Portfolio Manager to turn ideas into production-ready strategies.

The pod is led by a Senior Portfolio Manager with 15+ years of experience and a proven track record in alpha generation, strategy development, and risk management at top-tier quant firms. This is a unique opportunity to own the technology stack from day one, influence strategic direction, and help shape a high-performance team in a collaborative and intellectually rigorous environment.

Location

Dubai

• Technical Leadership & Architecture
• Design and maintain the trading system architecture, including components for data ingestion, signal generation, backtesting, execution, and risk management
• Make decisions on technology stack, performance optimization, and scalability
• Ensure the system supports reasonable latency, high-throughput, and fault-tolerant trading

• Team Leadership & Collaboration
• Help recruit and lead a small team of developers (sometimes quants as well) within the pod
• Work closely with the quant researchers and traders to understand strategy requirements and translate them into code
• Prioritize tasks and mentor junior developers or quant devs

• Strategy Implementation Support
• Build and maintain research infrastructure (e.g., backtesting frameworks, simulation environments, feature stores)
• Translate researchers  prototypes (e.g., in Python) into production grade code, often in C++, or C# for latency-sensitive components

• Execution & Infrastructure
• Optimize and support order execution systems, integrating with various exchanges or broker APIs
• Implement real-time risk checks, monitoring, logging, and alerting tools

• Data Engineering & Management
• Oversee the pipeline for ingesting, cleaning, and storing data (market, alternative, internal)
• Ensure data integrity and low-latency access for trading and research

• Dev Ops & Reliability
• Often take responsibility for deployment pipelines, version control, and production support
• Ensure high system availability and rapid recovery in case of failures

• Security & Compliance
• Make sure that the pod s infrastructure adheres to firm-wide compliance and security standards
• Ensure rigorous version control, code quality, and documentation standards
• Conduct thorough testing and debugging of software components, resolving any issues or discrepancies.

• 1st class Bachelor s or Master s degree in Computer Science, Mathematics, Physics, Engineering, or a related quantitative field
• Fluency in C++ or C# for performance-critical systems
• Proficiency in Python, especially for scripting, research integration, and data tools
• Solid understanding of algorithms, data structures, and multithreaded / concurrent programming
• Strong knowledge of SQL and modern database design (e.g., column stores, time-series DBs)
• Familiarity with software engineering best practices: version control (Git), unit testing, CI / CD, logging, monitoring, etc.
• Strong troubleshooting skills across distributed systems

• 3+ years of hands-on experience designing, building, and maintaining high-performance trading systems, ideally in a systematic equities or quant trading environment
• Proven experience in :
• Handling large-scale market data (e.g., normalization, feed handling, replay systems)
• Order routing and exchange connectivity, including FIX protocols and direct market access (DMA)
• Building event-driven architectures and real-time systems with tight SLAs
• Identifying and resolving performance bottlenecks, data inconsistencies, or system instability in production environments

• Excellent communication skills - able to interface directly with quant researchers and traders, translate requirements, and explain technical decisions
• Demonstrated initiative and ownership : able to drive projects independently, while collaborating effectively in a team setting
• Comfortable in fast-paced, iterative environments where priorities can shift quickly based on market conditions or research insights