Production Support Engineer - Trading Systems

Qube Research & Technologies

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT: * The successful candidate will join the Production Management team based in New York, providing high-touch support to the QRT trading desks and Risk managers with a dedicated focus on Risk and PnL systems.   * QRT trades across all major EMEA and US markets, and this role sits at the intersection of technology and front office operations.  * You will be the primary point of contact for the investigation and resolution of issues impacting real-time risk monitoring, daily PnL figures, and trade / positions reconciliation.   * You will work closely with traders, quants, and finance teams to ensure the integrity and availability of risk and PnL data throughout the trading day and at end of day. You will also liaise with internal development, quant research, and external counterparties to maintain a stable and accurate production environment.  Your present skillset: * Real-time risk support: Monitor and support intraday risk systems, ensuring live Greeks, exposure, and limit utilisation data are accurate and available to the front office throughout the trading day  * PnL production and reconciliation: Own the end-of-day PnL process, including identification and resolution of breaks between trader flash PnL and official finance PnL  * Trade and position reconciliation: Investigate and resolve position breaks between internal systems, prime brokers, and exchange/clearing houses  * Market data integrity: Ensure pricing and reference data feeds (EOD prices, vol surfaces, yield curves) used in risk and PnL calculations are correct and complete  * Explain PnL attribution: Work with traders and quants to explain PnL moves by decomposing into risk factors (delta, gamma, vega, theta, etc.)  * System availability: Ensure all risk and PnL components are operational before the start of each trading session; manage morning health checks and sign-off processes  * Incident management: Lead investigation and resolution of risk or PnL discrepancies, communicating clearly with traders and senior management under time pressure  * Process improvement: Develop scripts and tools to automate reconciliation, monitoring, and alerting workflows to reduce manual effort and improve accuracy  * Release management: Support the deployment of risk system and PnL platform releases, validating output integrity before and after changes  * Evening/weekend support: Provide on-call coverage for critical end-of-day and start-of-day processes, normally via remote access  Essential  * Minimum 2 years in a risk, PnL, or quantitative support role within a trading firm, hedge fund, or investment bank * Strong understanding of risk metrics: delta, gamma, vega, theta, DV01, and portfolio-level exposure aggregation  * Hands-on experience with PnL production workflows, including flash vs. official PnL reconciliation and attribution  * Familiarity with financial instruments across at least two asset classes (Equities, Futures, Commodities, FX, Fixed Income)   * Strong relational database skills – able to query and investigate data independently (SQL Server or Postgres preferred)  * ~1 year of scripting experience in Python, Bash, or PowerShell for automation and investigation tooling  * Excellent analytical and problem-solving skills with a methodical approach to root cause analysis  * Strong written and oral communication skills – able to explain technical issues clearly to traders and senior stakeholders  * High sense of ownership: proactive in following issues through to resolution without being chased  Base salary range for this position is $150,000 to $220,000 per year.  QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

Qube Research & Technologies

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT's collaborative mindset which enables us to solve the most complex challenges. QRT's culture of innovation continuously drives our ambition to deliver high quality returns for our investors. You'll help build and operate QRT's internal AI platform, enabling researchers, developers and data scientists to leverage LLM-powered tools effectively at scale. Working alongside experienced Platform Engineers, you'll contribute to production AI services including RAG pipelines, agentic workflows, retrieval infrastructure and internal APIs. This role is ideal for an early-career engineer or recent graduate with a strong foundation in AI and machine learning who is excited to bring cutting-edge models into production systems. YOUR FUTURE ROLE WITHIN QRT: AI PLATFORM DEVELOPMENT - * Build and enhance internal AI services, APIs and production applications. * Contribute to RAG pipelines, including document ingestion, embeddings and retrieval. * Support the deployment of transformer-based models and agentic workflows. * Design scalable, well-documented APIs for internal users. PLATFORM RELIABILITY & QUALITY -  * Improve service reliability, latency and evaluation frameworks. * Contribute to prompt management, testing and human-in-the-loop controls. * Build resilient AI systems with monitoring and fallback mechanisms. OPERATIONS & OBSERVABILITY - * Implement monitoring, tracing and quality metrics across AI services. * Support deployment, versioning and lifecycle management. * Participate in operational support and incident response alongside senior engineers. YOUR PRESENT SKILLSET: We value a combination of academic achievement, research and practical experience. We do not expect candidates to meet every requirement below. * Bachelor's, Master's or PhD in Computer Science, Machine Learning, Engineering, Mathematics or another quantitative field, or equivalent practical experience. * Strong foundation in AI and machine learning, including exposure to transformers and reinforcement learning. * Strong Python skills and an interest in building production-grade software. * Experience with PyTorch or another deep learning framework. * Understanding of LLM fundamentals, including prompting, context management and model limitations. * Experience building AI/ML applications or working with LLMs or other deep learning models. * Exposure to cloud platforms (e.g. AWS) and modern software engineering practices. * Strong communication skills and the ability to collaborate across technical and non-technical teams. NICE TO HAVE: * Experience deploying ML or LLM models into production. * Familiarity with RAG systems, vector databases and retrieval techniques. * Experience with agentic AI systems, workflow orchestration or LLM evaluation. * Understanding of embeddings, retrieval performance and human-in-the-loop systems. * Experience building APIs, data pipelines or observability tooling. * Contributions to open-source projects, research publications or ML competitions (e.g. Kaggle).   Base salary range for this position is $180,000 to $300,000 per year.  QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

Numeus

We are seeking an experienced DevOps Infrastructure Engineer to manage and maintain our cloud-based systematic trading infrastructure and build tools to enable and accelerate research. The ideal candidate will have extensive experience in software development tools, production management and cloud tooling in a systematic trading environment. Key Responsibilities: * Create, manage and maintain our production, research and trading infrastructure across multiple cloud regions * Optimize our low-latency systematic trading compute and network infrastructure * Support large research computing and modeling workloads with resilient, auto-scaling clusters and efficient hardware utilization * Troubleshoot and resolve any technical issues that arise, including server downtime, network connectivity problems, and cloud outages * Monitor system performance, and proactively identify and address any performance bottlenecks, security vulnerabilities, or other issues that could impact trading operations * Work collaboratively with quantitative researchers, traders, developers, and other stakeholders to understand their needs and ensure that the trading and research infrastructure meets their requirements Requirements: * 5+ years experience as an Infrastructure Engineer or similar role in a fast-paced environment, ideally buy-side systematic trading * Production experience with cloud technologies, ideally AWS. Certifications alone are not enough. * Extensive experience with Kubernetes, including large auto-scaling clusters, and highly available services, as well as knowledge of related GitOps tools such as FluxCD or ArgoCD * Hands-on production experience with Linux, including knowledge of installations, configurations, and troubleshooting * Religious about IaC, mastery of Terraform is required. Must have a passion for automation, and experience with relevant tools, such as Ansible. * Practical working knowledge of UDP, TCP/IP, routing protocols, VPN technologies, user-space kernel bypass networking. Ability to dive deep and understand the full network stack. * Experience with monitoring frameworks, such as Prometheus and Grafana * Self-starter with strong verbal and written communication skills * Ability to travel periodically between our offices in London, NYC, and Zug, Switzerland Are you keen to work in a well-resourced startup environment, where your ideas, experience, and drive to find creative solutions makes a difference? We’d like to hear from you. The base salary for this role is anticipated to be between $125,000 and $200,000. This anticipated base salary range is based on information as of the time this post was created. This role may also be eligible for additional forms of compensation and benefits, such as a discretionary bonus, health, dental and other benefits plans. Actual compensation will be carefully determined based on a number of candidate factors, including their skills, qualifications and experience.