Senior Real-Time Risk Platform Engineer

Jain Global (Hong Kong) Limited; Hong Kong; On-site; HKD 1,412,000 - 1,882,000; Full time

Job summary

Jain Global (Hong Kong) Limited seeks a Quantitative Developer for Risk Technology to own platforms capturing positions, computing risks, and delivering risk data to risk and portfolio managers in near real-time.

You will build low-latency services, data pipelines, APIs, and dashboards while modernizing legacy risk processes. Strong engineering disciplines and cross-team collaboration are essential in a fast-paced hedge fund environment.

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.
• 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.

Responsibilities

• Platform and Systems Engineering: Design, build, and own risk calculation and exposure aggregation services from position capture to delivered risk numbers.
• Develop real-time risk monitoring systems, including limit frameworks, breach detection, alerting, and drill-down interfaces.
• Build APIs and services (REST/gRPC, streaming) exposing risk data to downstream consumers.
• Deliver front-end tooling and dashboards for slicing exposure by strategy, desk, asset class, factor, and counterparty.
• Refactor and modernize legacy risk processes by 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 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 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 production code with numerical validation.
• Build tooling for backtesting, recalibration, and model-version comparison without heavy engineering involvement.
• Maintain pricing and sensitivity infrastructure and related libraries.
• Reliability, Performance, and Operations: End-to-end reliability — monitoring, alerting, runbooks, on-call, incident follow-up.
• Profile and optimize hot paths — vectorization, caching, concurrency, memory layout, distributed compute.
• Meet daily deadlines for overnight and intraday risk production with automated recovery and clear failure semantics.
• Build CI/CD, automated testing, infrastructure-as-code, and release processes for a high-stakes platform.
• Collaboration: Partner with Market Risk, Credit Risk, CRO office, and Portfolio Managers to translate requirements into software.
• Work with Front Office quant and trading tech 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 and investor due diligence with reliable data and documentation.
• Technical Leadership: Set engineering standards for risk stack — code review, testing, documentation, architectural direction.
• Mentor junior developers and raise delivery quality.
• Evaluate and adopt new technologies pragmatically when beneficial.

Skills

Python

C++

C#

Java

Rust

Distributed systems

API design

CI/CD

Testing

Performance

Concurrency

Time-series

Education

BS/MS in Computer Science or quantitative field

Tools

Kafka

Redis

Airflow

Dagster

Kubernetes

Docker

Cloud platforms

kdb+/q

ClickHouse

Arctic

Job description

Jain Global (Hong Kong) Limited seeks a Quantitative Developer for Risk Technology to own platforms capturing positions, computing risks, and delivering risk data to risk and portfolio managers in near real-time.

You will build low-latency services, data pipelines, APIs, and dashboards while modernizing legacy risk processes. Strong engineering disciplines and cross-team collaboration are essential in a fast-paced hedge fund environment.