Lead design, build, and support Python-based real-time risk and PnL services for Rates trading. Ensure performance, correctness, resiliency, CI/CD, observability, production support, and collaboration with traders, quants, DevOps, and platform teams. Drive adoption and safe use of enterprise AI-assisted engineering practices.
Description
About the TeamJ.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
The Rates Live Risk & PnL team delivers real-time trading risk and profit & loss capabilities, partnering closely with traders and desk strategists. You will contribute to critical components across the stack—from data ingestion and calculation services to UI and operational tooling—ensuring performance, correctness, and resiliency under tight timelines and high business impact.
Job Responsibilities- Design, develop, and support Python-based live risk and PnL applications used by Rates trading desks
- Work in a fast-paced trading environment, partnering closely with traders and stakeholders to translate business needs into robust technical solutions
- Build secure, high-quality production code with strong focus on correctness, performance, and operational stability
- Contribute to system design and implementation for real-time services, meeting non-functional requirements (latency, throughput, availability)
- Participate in production support, incident management, and continuous improvement of operational readiness (monitoring, alerting, runbooks)
- Collaborate with DevOps and platform partners to improve CI/CD, deployment automation, and environment reliability
- Identify and address technical debt and performance bottlenecks to improve platform scalability and responsiveness
- Collaborate effectively across functions (quants/strats, traders, product, other engineering teams) to deliver end-to-end solutions
- 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.
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Bachelor’s Degree in Computer Science, Cybersecurity, Data Science, or related disciplines
- Hands-on experience in application development, testing, and operational stability in production environments
- Strong proficiency in Python for building production services and performance-sensitive applications
- Working knowledge of real-time/distributed system concepts (e.g., concurrency, messaging patterns, caching, failure modes)
- Solid understanding of the Software Development Life Cycle (SDLC), engineering hygiene, and secure coding practices
- Experience with CI/CD, observability, and operational excellence (monitoring, alerting, troubleshooting)
- Strong problem-solving skills; ability to learn quickly and deliver high-quality outcomes under time pressure
- Effective communication skills and comfort partnering with front-office stakeholders
- 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
- Financial markets background (Rates products, risk, PnL, market data, trade lifecycle)
- Exposure to Deephaven (or similar real-time analytics/UI platforms), including awareness of installation/runtime dependencies (e.g., Java), environment setup, and operational considerations
- Experience with DevOps practices (deployments, release processes, environment management, performance testing)
- Understanding of UI programming (web or desktop) and collaborating across UI/backend boundaries
- Familiarity with Java and/or mixed-language environments where Python services interact with JVM-based components
- Experience with event-driven architectures and high-performance data pipelines used in front-office systems
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorganChase Singapore, Singapore, SGP Office
One@Changi City, Changi Business Park Central 1, Singapore, Singapore, 486036
Similar Jobs
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Leads strategic relationships with global and regional partners, combining pre-sales solution consulting, technical discovery, demonstrations, proof-of-concept leadership, solution architecture, AI adoption, business planning, and partner growth strategy. The role translates ServiceNow platform capabilities into scalable, industry-aligned offerings, supports executive-level engagements, coordinates specialist teams, and advances partner solutions from concept through commercialization.
Top Skills:
Ai AgentsNow AssistServicenow
Fintech • Payments • Financial Services
Lead and coach a Singapore-based software engineering team to build and scale Adyen's Global Cards platform across APAC. Translate product priorities into resilient, maintainable backend solutions, drive architecture and engineering quality, collaborate cross-functionally, and own credit card payments strategy and operational excellence.
Top Skills:
AuthorisationCard Scheme IntegrationsCredit Card PaymentsDistributed SystemsJavaObservabilityRoutingSettlementTesting
Fintech • Mobile • Payments • Software • Financial Services
Leads up to 10 Enterprise Support Specialists, overseeing performance, training, hiring, workflows, SLAs, schedules, and partner account support. Analyzes partner feedback and support data, escalates complex issues, manages improvement projects, and collaborates with Customer Success, Account Management, Servicing, and product teams to improve partner experience and operational processes.
What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
