Top Tech Jobs & Startup Jobs

Build scalable, high-performance systems for trade and position lifecycle management, reference data, reporting, and analytics. Develop automation for corporate actions, expiries, and cash flows; maintain data quality and system reliability; and support validation, monitoring, CI/CD, and production operations. Collaborate with trading, research, risk, operations, brokers, and fund administrators to translate business needs into reliable technical solutions.

Administer, secure, monitor, and optimize PostgreSQL databases across on-premises and cloud environments. The role manages backups, recovery, disaster recovery, high availability, capacity planning, upgrades, access controls, and performance tuning. It partners with engineers and business users to resolve database issues, translates requirements into solutions, automates administration tasks, and maintains operational documentation. Candidates need at least five years of production PostgreSQL administration experience plus Linux, SQL, scripting, security, and database operations expertise.

Technology interns contribute to production systems supporting quantitative research, trading, analytics, risk, security, infrastructure, or FPGA development. Responsibilities may include software development, hardware and system integration, security investigations, Linux performance analysis, automation, testing, and performance optimization. Interns work with engineers, researchers, and traders on defined technical projects during a 10-week summer program.

Design, deploy, configure, operate, and improve a bare-metal quantitative trading platform. Responsibilities include managing physical infrastructure, trading application environments, observability systems, and intent-driven platform management. Participate in on-call rotations, resolve critical production issues, collaborate with traders, researchers, developers, and service providers, and convert operational fixes into engineered solutions.

Design, deploy, configure, and operate a bare-metal trading platform spanning physical infrastructure, trading applications, observability systems, and intent-driven management. Participate in on-call support, troubleshoot critical production issues, collaborate with traders, researchers, developers, and service providers, and convert pragmatic fixes into engineered solutions. The role requires Linux expertise, scalable production systems experience, and strong computer science fundamentals.

Design, build, and optimize ultra-low-latency distributed trading systems in modern C++. Collaborate with quantitative researchers and traders to translate strategies into production systems, develop execution capabilities, and improve latency, scalability, reliability, and performance. Responsibilities include multithreaded systems programming, networking, Linux optimization, electronic trading connectivity, and potentially hardware acceleration using FPGA technology.

Design and develop high-performance C++ platforms, services, and infrastructure supporting ETF technology. Build data processing, messaging, connectivity, workflow, and integration components for real-time and reference data. Improve production-system performance, resilience, scalability, monitoring, and observability while collaborating with engineers, researchers, and business stakeholders. Contribute to architecture, testing, code quality, and long-term platform strategy.

Design, operate, and evolve QRT’s global AWS cloud network infrastructure. Responsibilities include building scalable and resilient network architectures, supporting cloud and datacenter connectivity, implementing infrastructure as code, evaluating AWS networking services, developing governance and observability standards, and resolving complex connectivity and performance issues. The role requires strong AWS networking, security, traditional networking, Terraform, and Python expertise, with collaboration across infrastructure, applications, quantitative research, and trading teams.

Discover, evaluate, onboard, and maintain financial datasets for quantitative research and trading, with emphasis on macro markets. Build Python tools and data pipelines to extract, clean, normalize, validate, and analyze data from multiple sources. Investigate data discrepancies, assess vendor APIs and offerings, improve dataset quality, and collaborate with researchers, traders, portfolio managers, vendors, and engineering teams.

Evaluate and onboard macro financial datasets for quantitative research and trading. Assess data coverage, quality, consistency, APIs, and delivery mechanisms; develop Python tools and pipelines to extract, clean, normalize, and analyze data; investigate discrepancies across providers; improve dataset quality; and collaborate with researchers, traders, vendors, and engineering teams to automate reliable data integration.