Senior Quantitative Equity Systems Developer

About the position What You’ll Do: Design, build, and operate cloud‑native platforms that run quantitative equity models across research, back‑testing, and production workflows Partner closely with portfolio managers, quantitative researchers, and traders to translate investment ideas into robust, scalable technology solutions Architect systems that support active equity portfolio construction, risk modeling, factor analytics, and execution workflows Integrate and work with carefully selected external vendor data provider solutions, ensuring reliable, performant, and well‑governed use of data. Collaborate with centralized enterprise technology teams to adopt and implement approved architectural patterns, platforms, and shared services Lead technical design decisions across distributed systems, data pipelines, and compute‑intensive workloads Drive engineering best practices around resilience, observability, performance, and security in a front-office environment Mentor and influence other engineers, raising the overall technical bar of the team Ability to be a change agent, embrace innovation and shape people, process and technology view to solving complex problems. Contribute to the long‑term technology strategy for quantitative and systematic investing platforms What we’re Looking For: This role is designed for candidates who are equally comfortable in investment conversations and deep technical discussions. You sit with the investment team, not behind layers of abstraction. It offers a rare opportunity to operate at the center of technology-driven active equity investing. You will help shape the architecture and direction while embracing and fostering a culture that values technical excellence, intellectual curiosity, and close partnership with the business. If you are a senior engineer or technical lead who enjoys working on complex, high-stakes systems, wants to be deeply embedded in the investment process, and brings both engineering rigor and investment domain knowledge, we would love to hear from you!

Responsibilities

• Design, build, and operate cloud‑native platforms that run quantitative equity models across research, back‑testing, and production workflows
• Partner closely with portfolio managers, quantitative researchers, and traders to translate investment ideas into robust, scalable technology solutions
• Architect systems that support active equity portfolio construction, risk modeling, factor analytics, and execution workflows
• Integrate and work with carefully selected external vendor data provider solutions, ensuring reliable, performant, and well‑governed use of data.
• Collaborate with centralized enterprise technology teams to adopt and implement approved architectural patterns, platforms, and shared services
• Lead technical design decisions across distributed systems, data pipelines, and compute‑intensive workloads
• Drive engineering best practices around resilience, observability, performance, and security in a front-office environment
• Mentor and influence other engineers, raising the overall technical bar of the team
• Ability to be a change agent, embrace innovation and shape people, process and technology view to solving complex problems.
• Contribute to the long‑term technology strategy for quantitative and systematic investing platforms

Requirements

• Minimum of ten years related work experience, with at least five years of development experience.
• Prior Investment Systems experience required.
• Undergraduate degree or equivalent combination of training and experience.
• Extensive experience building large-scale, production-grade software systems in complex domains.
• Strong understanding of quantitative or active equity investing, including concepts such as factors, signals, portfolio optimization, risk, and execution.
• Demonstrated success working in front-office, investment-aligned technology roles.
• Deep expertise in modern software engineering, including object‑oriented and/or functional programming paradigms, distributed systems and data‑intensive architectures, and cloud‑native platforms such as containerization, orchestration, and managed cloud services.
• Strong proficiency in Python and modern data processing and numerical computing tools (e.g., Polars).
• Familiarity with machine learning and AI-assisted development techniques, including the use of AI or agentic coding tools (e.g. Claude Code) to improve research and engineering productivity.
• Experience building and supporting AWS architecture including services such as EC2, CloudWatch, ECS, Sage Maker, ECS, Steps Functions, Lambda and Postgres.
• Experience operating in environments where system performance, reliability, and correctness are business critical.
• Direct experience supporting quantitative equity, systematic, or multi-factor investment strategies.
• Familiarity with research and back-testing platforms, market and alternative data, and model lifecycle management.

Nice-to-haves

• Graduate degree preferred.
• Exposure to both legacy enterprise systems and modern engineering stacks, with the ability to modernize thoughtfully.
• Prior experience working side‑by‑side with investment teams on a trading floor or similar front‑office setting.
• Strong knowledge of equity trading and execution systems.

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