Quantitative Developer

Job description

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.

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

Principal responsibilities

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.

DevOps & 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.

Required technical skills

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 databases)

Familiarity with software engineering best practices: version control (Git), unit testing, CI/CD, logging, monitoring, etc.

Strong troubleshooting skills across distributed systems

Required experience

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

Highly valued relevant attributes

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