The Risk Systems Engineer role at Clearwater Analytics focuses on designing, implementing, and operationalizing quantitative analytics within the Beacon Platform ecosystem.
The primary objective of this role is to help build and evolve a Risk-as-a-Service framework — packaging market data, reference data, pricing models, and risk analytics into scalable, well-structured, and easily consumable services across asset classes. This requires a strong understanding of financial products and risk concepts, combined with disciplined software engineering practices.
This role is part of a small, focused team of experienced and highly capable engineers who work collaboratively and move quickly while maintaining high standards of quality and rigor. The environment values ownership, clarity of thinking, and thoughtful execution.
The engineer will collaborate with financial engineers, quants, product teams, and clients to translate quantitative methodologies into reliable production systems. The role requires continuous learning, clear communication, and the ability to balance financial intuition with engineering discipline.
Clearwater embraces modern development practices, including the responsible use of generative AI to enhance productivity, validation, and engineering workflows. Candidates should be open to leveraging AI tools as part of next-generation quantitative platform development.
Across all levels, a successful Financial Engineer will demonstrate strong analytical reasoning, clean and maintainable coding practices, effective cross-functional collaboration, and a proactive problem-solving mindset.
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Design, build, deploy, and maintain scalable Risk-as-a-Service components that integrate market data, reference data, pricing models, and risk analytics.
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Collaborate closely with quantitative researchers to productionize models and ensure robust implementation within the Beacon platform.
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Package quantitative analytics into structured, reusable, and client-consumable services.
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Develop and maintain high-quality Python and C++ components supporting pricing and risk workflows.
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Contribute to market data ingestion, curve construction, calibration, and analytics orchestration processes.
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Ensure that quantitative logic is reliable, well-tested, and production-ready through strong automated testing practices (unit, integration, regression, validation).
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Break down complex financial and computational problems that require cross-team collaboration and structured engineering solutions.
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Participate in architecture and design discussions focused on scalability, performance, reliability, and maintainability of analytics systems.
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Troubleshoot and resolve production issues related to data, valuation, or risk services.
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Leverage generative AI tools responsibly to improve development efficiency, documentation quality, testing coverage, and validation workflows.
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Coordinate with cross-functional teams to ensure seamless integration of analytics services across systems.
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Understand and respond to internal and external stakeholder needs with clarity and timeliness.
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Mentor junior team members and promote best practices in quantitative engineering.
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Any other reasonable activity required by management.
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Proficiency in Python
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Experience with a typed, object-oriented programming language such as C++, Rust or systems language like C
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Strong understanding of financial markets, derivatives, and risk management concepts
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Experience working with trading desks, risk management teams, or quantitative analytics functions
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Ability and willingness to leverage generative AI–based tools, including agentic programming workflows, to enhance productivity and deliver measurable value
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Ability to translate quantitative concepts into production-grade software
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Understanding of how market data, reference data, and risk analytics interact within financial systems
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Strong knowledge of software development methodologies, tools, and architectural patterns
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Experience with automated testing in analytical or computational systems
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Comfort collaborating closely with quantitative researchers
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Exceptional analytical and problem-solving skills
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Strong teamwork, organizational, and communication skills
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Excellent attention to detail and documentation skills
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Commitment to continuous learning and improvement
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Degree in Financial Engineering, Computer Science, Mathematics, Physics, Engineering, or related quantitative field
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5+ years of experience in quantitative development, financial engineering, risk analytics, or financial systems engineering
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CFA, FRM, or advanced quantitative degree preferred
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Experience with platforms such as Beacon, SecDB, Athena, Quartz, or similar quantitative risk systems is a strong plus
