Role Description :

Lead the Design, development, and optimization of low-latency, high-performance new generation engine and analytics systems for crypto and multi-asset markets. Work closely with quant researchers and business teams to deliver scalable, fault-tolerant, and future-ready infrastructure.

Key Responsibilities :

- Low-latency and optimize real time data pipelines : ingestion, feature-engineering, signal generation, execution.

- Develop and maintain modules to handle exchange connectivity (WebSocket/FIX).

- Oversee time-series databases and high-throughput storage.

- Implement GPU/FPGA acceleration and hybrid AI/ML-QC modules.

- Ensure system resilience, monitoring, and ultra-low-latency performance, and fault-tolerant production deployments.

Education & Qualification :

Experience : 8 to 12+ years overall in software engineering / low-latency systems.

- At least 8+ years in trading domain / HFT / low-latency finance systems.

- Proven track record of leading development teams.

Mandatory :

- B.Tech / M.Tech in Computer Science, Electronics, Electrical Engineering, IT, or Applied Mathematics from IITs, NITs, IIITs, BITS, or other Tier-1 institutes.

- M.Sc / M.Tech in Data Science, Computational Mathematics, or Statistics with strong programming exposure.

Preferred :

- Ph.D. in Computer Science, High-Performance Computing, or Quantitative Finance.

- CQF (Certificate in Quantitative Finance) or equivalent.

- Cloud/Infra certifications (AWS/GCP/Azure) with low-latency and HPC focus.

Key Skills :

- Advanced C++ / Rust / Go / Python/linux coding for low-latency trading infra.

- Time-series DB experience.

- Deep knowledge of data structures, databases , time-sync, and data compression.

- Distributed systems, GPU/FPGA acceleration, network optimization.

- Exposure to quantum SDKs.

- Prior experience in HFT/prop desk/crypto infra, exchange connectivity is highly desirable.

- Hands on Development experience is a must.

KPIs :

- Latency dashboards and monitoring systems.

- Uptime & fault tolerance (>99.99%).

- Speed of new technology adoption and integrations in development stack

- Reduction in infra costs vs performance.