Role Summary
We are building a new quantitative engineering function from the ground up in Singapore. This role is for a midsenior Quant Developer who can ship production-grade trading and risk systems, work directly with traders and quants, and help establish the engineering standards and architecture that the team will scale on.
You will sit close to the trading business, own core components end-to-end, and play a defining role in how we build and operate a professional-grade digital asset trading stack.
Key Responsibilities
- Build and maintain low-latency, production trading infrastructure and quantitative tooling for digital assets (spot, derivatives, perpetuals, options where relevant).
- Implement, optimize, and productionize pricing, execution, risk, and PnL/portfolio analytics.
- Partner with traders/PMs to translate strategy requirements into robust, measurable, testable systems.
- Design and implement market data pipelines (real-time + historical), including normalization, storage, and replay tooling.
- Build execution components: order routing, smart order logic, throttling, exchange connectivity, and post-trade controls.
- Develop and maintain risk controls: limits, kill-switches, exposure, margin, liquidation scenarios, and intraday monitoring.
- Own the SDLC for critical components: code quality, testing, CI/CD, observability, incident response, and post-mortems.
- Contribute to team build-out: setting standards, mentoring, shaping hiring profiles, and helping define the technical roadmap.
Requirements (Must Have)
- Minimum 8 years of professional experience in quant development, trading systems engineering, or a closely related front-office engineering role.
- Strong coding ability in C++ and/or Java for performance-critical systems, plus Python for research tooling, analytics, or automation.
- Proven track record delivering production systems in trading environments (latency, reliability, monitoring, on-call realities).
- Strong understanding of market microstructure, execution workflows, and the lifecycle of a trade (orders, fills, positions, PnL).
- Solid foundations in data structures, multithreading/concurrency, networking, and performance optimization.
- Experience working closely with trading desks, quants, or PMs in fast-moving environments.
- Strong problem-solving under pressure and ability to operate with incomplete requirements.
Nice to Have
- Direct experience in digital assets (exchange APIs, perpetuals funding, liquidation mechanics, venue behaviour, custody/wallet flows).
- Experience building exchange connectivity and market data capture at scale.
- Familiarity with kdb+/q, Redis, Kafka, time-series databases, or high-performance data storage patterns.
- Understanding of derivatives/option pricing, Greeks, and risk, even if you are not the model author.
- Cloud + containerization experience (AWS/GCP, Docker/Kubernetes), plus modern observability (Prometheus/Grafana, OpenTelemetry).
- Experience hiring, mentoring, or leading small engineering pods in trading contexts.
What Success Looks Like (First 612 Months)
- Deliver core building blocks that become the backbone of the trading stack: market data, execution, risk controls, monitoring.
- Establish engineering practices that scale (testing, deployments, incident processes, performance baselining).
- Help recruit and shape the initial quant engineering team in Singapore.
- Become a trusted technical partner to trading leadership.
Working Style
- High ownership, low ego: you build, you measure, you fix.
- Pragmatic and commercial: the goal is robust trading outcomes, not academic perfection.
- Comfortable with ambiguity and fast iteration, while still enforcing discipline where it matters (risk, controls, production quality).
