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Senior Python Engineer needed to build scalable risk and PnL systems for rates trading in Singapore.
Lead development of AI‑assisted tooling, risk metrics, and data pipelines across trading desks and back‑office.
Lead Software Engineer - Risk Technology
Location
Singapore
Description
We are seeking an experienced Senior Python Developer to join our Athena Rates development team to work on a Risk and PnL delivery for Rate Line of Business. In this role, you will design, develop, and integrate sophisticated solutions that support trading desks and back office functions across rates products. You will work at the intersection of technology and finance, delivering high-impact systems that enable critical risk management and profit & loss analysis for our trading operations.
As a Senior Python Developer on our team, you will build and maintain robust software solutions for rates trading activities. You will collaborate closely with quantitative analysts, traders, risk managers, and Equities technology teams to integrate systems across middle and back office processing. Your work will directly support trading operations across multiple Rates product types starting with Swap Derivative products and Options products.
Job responsibilities
Develop scalable, performant code that handles large volumes of market data and complex financial calculations. This includes implementing risk metrics, PnL attribution frameworks, and data pipelines that connect trading systems with downstream consumers.
Participate in architectural decisions, code reviews, and technical design sessions, contributing your expertise to shape the evolution of this automated risk platform.
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied Python experience
Bachelor’s Degree in Computer Science or equivalent
Solid understanding of software engineering principles including object-oriented design, testing methodologies, and version control practices
Demonstrated ability to write clean, maintainable code and work effectively within large, complex codebases
Strong verbal and written communication skills with ability to articulate technical concepts to both technical and non-technical stakeholders
Proven ability to gather requirements from business users and collaborate across multiple teams and functions
Capability to translate business needs into technical solutions and explain technical constraints in business terms
Willing to understand and work on legacy applications when required
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Preferred qualifications, capabilities, and skills
Prior experience with other financial risk stack platforms such as SecDB, Quartz, or Athena
Strong preference for candidates with financial services background
Knowledge of rates products including Swaps, Securities, Options, and Repo
Familiarity with risk methodologies and PnL calculation frameworks
Experience with distributed systems and real-time data processing
Proficiency with relational and NoSQL databases
Knowledge of modern development practices including CI/CD pipelines and containerization
Exposure to quantitative finance concepts and market risk measures
Understanding of regulatory reporting requirements in financial services
Working knowledge of usage of Agentic AI in Software analysis , development and testing