Job Title

Role Overview:Act as KXs subject-matter expert at the intersection of quantitative trading, high-performance compute (HPC) and AI. Partner with front-office quants and infrastructure leads at global banks, exchanges and HFT firms to maximise speed-to-insight while minimising micro-seconds.Core Responsibilities:Analyse existing trading-system architectures and propose sub-s improvements leveraging KDB+/q, GPU/FPGA acceleration and state-of-the-art networking (RDMA, RoCE, 25-400 GbE, hollow-core fibre).Design and benchmark AI/ML inference pipelines (CUDA, Triton, Xilinx Vitis AI) for market-making, signal generation and anomaly detection.Advise on data-layout, compression and tiered storage to reduce latency and footprint.Collaborate with product and sales to create technical collateral and lead deep-dive workshops with quants/CIOs.Stay ahead of regulatory (MiFID II, SEC, MAS) and market-microstructure changes impacting low-latency AI.Preferred Qualifications:8 + yrs in front-office quant, electronic-trading or HPC engineering roles.Proven optimisation of ultra-low-latency systems (Strong coding skills in C/C++, CUDA and Python; familiarity with PyTorch/TensorRT.In-depth knowledge of market data feeds, order-entry protocols (FIX, OUCH, ITCH) and real-time risk controls.Hands-on experience with KDB+, tick and proprietary column-stores.Nice-to-Have:Exposure to AI agent frameworks for trade-execution or smart-order-routing.Publications or patents in time-series ML, event-stream processing or hardware acceleration.STEM postgraduate degree (e.g., Financial Engineering, Computer Engineering, Physics).