Equity Derivatives Risk Developer

Job Description:

Quantitative Developer – Risk Technology

Position Overview

We are seeking a strong software engineer to build and own the equity-volatility risk platform for our global hedge fund. This engineering-first role owns the systems that capture options, futures, swaps and cash equity positions, compute the full volatility greek surface across every book, and deliver exposure and limit information to volatility PMs and risk managers in near real time. Working alongside the quantitative analysts and researchers who own the vol models and beta framework, the engineer makes those models run correctly, fast, and reliably at firm scale — turning per-book risk snapshots into clean, aggregated, drill-downable exposure PMs trust every trading day, across low-latency services, large-scale data pipelines, distributed compute, and the APIs and interfaces on top of them.

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 existing 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.

- 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

- 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 Risk Managers 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.

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

Software Engineering (Primary)

- 5+ years building and operating production systems, with deep expertise in Python and at least experience in one systems language

- 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.

Data and Infrastructure

- Proficiency with SQL and analytical or columnar stores

- 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.

Domain Knowledge

- 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.

Education

- BS/MS in Computer Science, Engineering, Mathematics, Physics, or a related quantitative field. An advanced degree is welcome but strong engineering experience matters more.

Soft Skills

- 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: London

Compensation:

Jain Global offers a total compensation package which includes a base salary, discretionary bonus, and comprehensive benefits. The estimated base salary range for this position is £150,000- £170,000 which is specific to London and may change in the future. When finalizing an offer, we take into consideration an individual’s experience level and the qualifications they bring to the role to formulate a competitive total compensation package.

We are an Equal Opportunity Employer

As an employer, we believe every individual brings with them unique diversity of thought and perspectives to meaningfully enrich perspectives of Jain Global teams to drive competitive performance. We believe an inclusive environment can yield exceptional contributions.