AI-Driven Low-Latency Trading Systems Engineer

Tokka Labs; Singapore; On-site; SGD 150,000 - 210,000; Full time

Job summary

Tokka Labs in Singapore seeks a Trading Systems Engineer to build low-latency systems powering on-chain and traditional markets. You will work with quantitative traders and researchers to push performance, reliability, and AI-driven enhancements on the trading stack.

You will shape how AI agents are integrated into the SDLC, set rules for autonomous actions on the live path, and mentor the team on engineering practices that enable faster, safer execution.

Qualifications

• Proven track record in building low-latency systems for algorithmic trading.
• Strong understanding of trading system architecture and market connectivity.
• Experience collaborating with traders or researchers on strategy or tooling.
• Hands-on system-level performance tuning, monitoring and debugging.
• Genuine interest in AI and deploying agents in production.

Responsibilities

• Design and develop low-latency, high-throughput systems for trade execution, market data, and connectivity.
• Optimize performance and ensure operational stability through profiling and architectural improvements.
• Lead by example in using AI agents to ship faster while maintaining reliability.
• Shape the self-learning loops in the SDLC: evals, telemetry, and feedback signals.
• Define acceptable autonomy: which agents can act and where human review is required.
• Collaborate with quantitative traders to translate ideas into production-grade systems and deploy AI-driven enhancements.

Skills

Low-latency design

Algorithmic trading

AI in engineering

Performance tuning

Tools

C/C++

Linux

Profiling tools

Job description

Tokka Labs in Singapore seeks a Trading Systems Engineer to build low-latency systems powering on-chain and traditional markets. You will work with quantitative traders and researchers to push performance, reliability, and AI-driven enhancements on the trading stack.

You will shape how AI agents are integrated into the SDLC, set rules for autonomous actions on the live path, and mentor the team on engineering practices that enable faster, safer execution.