Quantitative Developer

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 DBs)
• 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