We are looking for a Trade Operations Engineer to take ownership of our risk, middle-office, and back-office systems. This role sits at the intersection of trading, engineering, and operations, and is critical to the reliability and scalability of the firm.

You will work closely with quantitative researchers, traders, and infrastructure, building and maintaining the systems that ensure trades are correctly captured, reconciled, and monitored in real time.

The role is hands-on and end-to-end. You will be responsible for designing, building, and operating full-stack applications that support trade reconciliation, risk monitoring, and operational workflows across both AWS and bare-metal environments.

What You’ll Be Doing

• Designing and building full-stack applications for risk monitoring and middle/back-office workflows using Java and React
• Owning trade reconciliation pipelines, ensuring accuracy and consistency across multiple systems and venues
• Developing operational tooling and monitoring to support live trading and post-trade processes
• Working closely with infrastructure to support systems running across AWS and colocated bare-metal servers
• Troubleshooting and maintaining trading applications, primarily in Java, with some interaction with C++ components
• Investigating and resolving live production issues related to trade flow, clearing, and risk limits
• Improving system reliability, observability, and operational efficiency over time

What You Need

Finance Experience: You have prior professional experience as a software engineer within the finance industry. Experience in HFT, proprietary trading, or systematic trading environments is a strong advantage.

Technical Stack: Strong full-stack engineering experience, with Java on the back-end and React on the front-end. You are comfortable owning both application logic and user-facing components.

Domain Knowledge: You understand post-trade workflows and operational processes, including trade reconciliation, clearing, and real-time risk monitoring. You are comfortable working with trade lifecycle data and debugging inconsistencies.

Systems Environment: You are comfortable working in Linux environments and collaborating with infrastructure teams. Experience working across cloud (AWS) and bare-metal or colocated environments is beneficial.

C++ Familiarity: You do not need to build low-latency systems in C++, but you should be comfortable reading, debugging, and making targeted changes in existing C++ codebases.

Ownership & Mindset: You take ownership of systems end-to-end, from development through to production support. You are pragmatic, detail-oriented, and comfortable working in a fast-paced trading environment where systems must be reliable under pressure.

HFT Software Developer – Junior & Senior Levels

About DeepFin Research

DeepFin Research is a proprietary high-frequency trading (HFT) firm powered by cutting-edge Deep Learning (DL) and Deep Reinforcement Learning (DRL). We've brought on teammates from Nvidia, DeepMind, CitSec, Graviton, Tower, Jump, and others, and are aggressively working across cutting edge AI research and traditional quant research methods to monetise our AI generated signals across the global financial markets.

The Role

We are looking for exceptional HFT software engineers to build our HFT trading infrastructure across global finanacial markets, including different asset classes, end-to-end from the ground up. This will include working across connectivity, market data, execution, risk, and building high performance high throughput C++ systems.

Responsibilities

• Design, implement, and optimize ultra-low-latency, zero-allocation trading engines in modern C++.
• Develop and maintain market data handlers and execution gateways utilizing protocols like FIX, OUCH, ITCH, and raw UDP multicast.
• Optimize system critical paths through OS-level tuning, CPU pinning, cache-line optimization, and NUMA-aware programming.
• Interface with hardware-accelerated components, working alongside FPGA engineers to integrate PCIe/DMA data pipelines.
• Implement kernel-bypass networking solutions (e.g., Solarflare OpenOnload, DPDK) to minimize network stack latency.
• Collaborate directly with AI researchers and quantitative traders to deploy complex quantitative models into strict, latency-sensitive production environments.
• Work end-to-end on projects from the ground up – this is not a role to focus on specialised parts of the infrastructure stack, but rather to see projects through end-to-end.

Ideal Candidate Profile

• 1–3 years of experience in low-latency software engineering for Junior candidates; 3–10+ years for Senior candidates.
• Exceptional expertise in C++ with a deep understanding of lock-free data structures, custom memory allocators, and hardware architecture.
• Proven experience building systems in HFT or highly concurrent, real-time computing environments.
• Strong grasp of Linux internals, network programming (TCP/IP, UDP), and performance profiling tools (e.g., perf, VTune).
• Solid understanding of futures markets microstructure; exposure to FX and options markets is a strong plus.
• Entrepreneurial mindset with the communication skills required to thrive in a fast-paced, highly collaborative environment, preferring end-to-end ownership over extreme specialization.