Quantitative Developer, Risk Technology

Location: New York, New York, United States

Base salary: $220,000–$250,000 per year, plus discretionary bonus and comprehensive benefits.

Company

hirify.global is a multi-strategy investment firm founded in July 2024, with more than 400 employees and offices in New York, Houston, London, Singapore, and Hong Kong.

What you will do

• Design, build, and own risk calculation, exposure aggregation, limit monitoring, breach detection, alerting, and drill-down systems.
• Develop REST/gRPC and streaming APIs, front-end tools, and dashboards for risk managers and portfolio managers.
• Build resilient pipelines and analytical data stores for positions, trades, market data, reference data, counterparty exposures, historical risk, stress replays, and time-travel queries.
• Integrate with prime brokers, clearing venues, execution platforms, and market data vendors while maintaining consistency across risk, Front Office, and Finance systems.
• Productionize VaR, stress, scenario, factor exposure, sensitivity, margin, pricing, and valuation infrastructure, including model backtesting and version comparison tools.
• Own reliability, performance, CI/CD, testing, infrastructure as code, incident response, technical standards, and mentoring for the risk technology platform.

Requirements

• BS/MS in Computer Science, Engineering, Mathematics, Physics, or a related quantitative field. An advanced degree is welcome, but strong engineering experience is more important.
• 5+ years building and operating production systems, with deep Python expertise and at least one systems language: C++, C#, Java, or Rust.
• Strong knowledge of distributed systems, concurrency, service design, API design, automated testing, code review, CI/CD, observability, and infrastructure as code.
• Experience with profiling, benchmarking, latency and throughput optimization, vectorization, caching, concurrency, memory layout, and distributed or grid compute.
• Proficiency with SQL, analytical or columnar stores, and time-series technologies such as kdb+/q, ClickHouse, Arctic, or similar.
• Experience with streaming and messaging systems such as Kafka or Redis, and workflow orchestration using Airflow, Dagster, or equivalent schedulers.
• Hands-on experience with containers, Kubernetes, at least one major cloud platform, and grid or distributed compute frameworks.
• Experience handling large-scale data where correctness and timeliness matter, preferably in a hedge fund, asset manager, investment bank, or similar institution supporting risk, valuation, or front-office systems.
• Working familiarity with multi-asset instruments, derivatives, VaR, stress testing, sensitivities, limits, margin, financing, and interpreting model inputs and outputs.
• Pragmatic problem-solving, attention to detail under time pressure, clear communication with risk managers and traders, proactive ownership, and comfort in a demanding, fast-moving environment.

Culture & Benefits

• End-to-end ownership of platforms used for daily trading and risk management.
• Direct proximity to risk managers and portfolio managers with immediate visibility into business impact.
• Engineering work focused on latency, scale, correctness, and modern infrastructure.
• Exposure to multiple regions, asset classes, and markets.
• Comprehensive benefits, discretionary bonus, and opportunities for growth and technical leadership.