Job Description

Quantitative Developer – Risk Technology

Global Hedge Fund | Singapore / Hong Kong

Position Overview

We are seeking a strong software engineer to join the Risk Technology team of our global hedge fund. This is an engineering-first role: you will own the platforms that capture positions, compute and distribute risk, and put exposure and limit information in front of risk managers and portfolio managers in near real time. The work spans low-latency services, large-scale data pipelines, distributed compute, and the APIs and interfaces that sit on top of them. You will work alongside quantitative risk analysts who own the models — your job is to make those models run correctly, fast, and reliably at firm scale, across every asset class we trade.

Key Responsibilities

Platform and Systems Engineering

Design, build, and own the firm's risk calculation and exposure aggregation services, from position capture through to delivered risk numbers.

Develop real-time and intraday risk monitoring systems, including limit frameworks, breach detection, alerting, and drill-down interfaces.

Build well-documented APIs and services (REST/gRPC, streaming) that expose risk data to downstream consumers across the firm.

Deliver front-end tooling and dashboards that let risk managers slice exposure by strategy, desk, asset class, factor, and counterparty.

Refactor and modernize legacy risk processes, replacing batch, spreadsheet, and manual steps with tested, version-controlled services.

Data Engineering and Integration

Build resilient pipelines for positions, trades, market data, reference data, and counterparty exposures, with automated validation, lineage, and reconciliation.

Own time-series and analytical data stores supporting historical risk, stress replays, and time-travel queries.

Integrate with prime brokers, clearing venues, execution platforms, and market data vendors, handling schema drift and vendor outages gracefully.

Ensure consistency of pricing, position, and P&L data between risk systems and Front Office and Finance platforms.

Analytics Delivery

Productionize risk models supplied by Risk Management and Research — VaR, stress and scenario frameworks, factor exposures, sensitivities, and margin analytics.

Translate research prototypes into performant, tested, maintainable production code with clear numerical validation.

Build the tooling that lets model owners backtest, recalibrate, and compare model versions without engineering involvement.

Maintain pricing and sensitivity (Greeks) infrastructure and the libraries that risk and valuation both depend on.

Reliability, Performance, and Operations

Own the reliability of risk systems end to end: monitoring, alerting, runbooks, on-call, and incident follow-up.

Profile and optimize hot paths — vectorization, caching, concurrency, memory layout, and distributed or grid compute workloads.

Meet hard daily deadlines for overnight and intraday risk production, with automated recovery and clear failure semantics.

Build out CI/CD, automated testing, infrastructure as code, and release processes for a platform that cannot silently produce wrong numbers.

Collaboration

Partner with Market Risk, Credit Risk, the CRO's office, and Portfolio Managers to turn requirements into shipped software.

Work closely with Front Office quant and trading technology teams on shared pricing, position, and market data infrastructure.

Collaborate with enterprise IT, data, and platform teams on cloud, networking, security, and compute capacity.

Support regulatory reviews, investor due diligence, and internal risk governance with reliable data and clear technical documentation.

Technical Leadership

Set engineering standards for the risk stack: code review, testing, documentation, and architectural direction.

Mentor junior developers and raise the bar on delivery quality across the team.

Evaluate new technologies pragmatically and lead their adoption where they earn their keep.

Qualifications

BS/MS in Computer Science, Engineering, Mathematics, Physics, or a related quantitative field. An advanced degree is welcome but strong engineering experience matters more.
8+ years building and operating production systems, with deep expertise in Python and at least one systems language (C++, C#, Java, or Rust).
Strong grounding in distributed systems, concurrency, service design, and API design; you have owned systems in production, not just written code for them.
Solid engineering discipline: automated testing, code review, CI/CD, observability, and infrastructure as code.
Comfortable with performance work — profiling, benchmarking, and reasoning about latency and throughput rather than guessing.
Proficiency with SQL and analytical or columnar stores, plus time-series technologies (kdb+/q, ClickHouse, Arctic, or similar).
Experience with streaming and messaging systems (Kafka, Redis, or equivalent) and workflow orchestration (Airflow, Dagster, or in-house schedulers).
Hands-on experience with containers, Kubernetes, and at least one major cloud platform, alongside grid or distributed compute frameworks.
Track record handling large-scale data volumes where correctness and timeliness both matter.
Experience at a hedge fund, asset manager, investment bank, or similar institution, ideally supporting risk, valuation, or front-office systems.
Working familiarity with multi-asset instruments and derivatives, and with how risk is measured and monitored in practice — VaR, stress testing, sensitivities, limits, margin, and financing.
You do not need to derive the models, but you should be able to read them, reason about their inputs and outputs, and spot when a number looks wrong.
Awareness of relevant reporting requirements (e.g., Form PF, AIFMD, EMIR, position and short-sale disclosures) across jurisdictions is a plus.
Pragmatic problem solver with high standards for correctness and attention to detail under time pressure.
Clear communicator, able to work directly with risk managers and traders and translate between business need and technical design.
Self-motivated, proactive, and comfortable owning systems in a demanding, fast-moving environment.

Why Join Us

Ownership: Take end-to-end responsibility for platforms the firm relies on every trading day.
Proximity to the Business: Sit with risk managers and portfolio managers; see the impact of your work immediately.
Engineering Depth: Hard problems in latency, scale, and correctness, on modern infrastructure with real budget behind it.
Global Exposure: Operate within a world-class organization spanning multiple regions, asset classes, and markets.
Career Development: Join a firm that values expertise, initiative, and innovation, with opportunities for growth and leadership.

Location & Compensation

Location: Singapore / Hong Kong

Compensation: Competitive salary with performance-based bonuses and benefits.

Jain Global jobs

Quantitative Developer, Risk Technology

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