Senior Lead Software Engineer - Python - Real-Time Risk & PnL | Front Office
Join us to build the real-time engine behind one of the world’s largest Credit Trading franchises. You’ll shape how billions move, architecting technology that drives revenue growth and empowers traders to compete and win. At JPMorganChase, we invest in your growth, offering opportunities to lead, innovate, and make a direct impact. Work alongside quants, traders, and product leaders in a fast-paced, collaborative environment. Your expertise will help us push the limits of what’s possible in global markets.
As a Senior Lead Software Engineer in Global Credit Trading Technology, you will architect and deliver real-time risk and P&L systems for the Front Office. You will collaborate closely with trading desks and quantitative analysts to design solutions that drive market performance. Your work will directly influence trader decisions and firm profitability. You will lead technical direction, mentor talent, and champion modern frameworks and cloud-native best practices. This role offers the opportunity to innovate and shape the future of credit trading technology.
Job Responsibilities:
- Architect and deliver low-latency, real-time streaming and calculation engines for trading platforms
- Lead technical direction across engineering teams and mentor talent
- Champion modern frameworks and cloud-native best practices
- Partner with quantitative analysts and trading desks to translate complex requirements into scalable solutions
- Drive adoption of AI tooling, event-driven architectures, and next-generation cloud platforms
- Collaborate with traders and product leaders to enhance pre-trade pricing, eTrading execution, and live position management
- Ensure systems meet sub-second latency requirements for risk and P&L calculations
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
- Shape product strategy and influence platform evolution
- Foster a culture of innovation and continuous improvement
Required Qualifications, Capabilities, and Skills:
- Expertise in Python and cloud-native development (Kubernetes, AWS/GCP)
- Experience with AI/ML tooling
- Proven ability to build real-time, low-latency systems for trading or pricing workflows
- Strong data engineering and analytics skills
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
- Front Office domain knowledge: post-trade lifecycle, live risk, P&L, pricing across Credit products
- Background in computer science, engineering, or mathematics with hands-on system design and delivery
- Ability to translate complex requirements into production-grade solutions
- Effective collaboration and communication skills
- Adaptability in fast-paced environments
Preferred Qualifications, Capabilities, and Skills:
- Mastery of distributed systems: microservices, event-driven architectures, Kafka, AMPS, TibRV
- Fluency with time-series databases, NoSQL, caching layers, and SQL optimization for trading data
- Experience translating quantitative models into production systems
- Technical leadership in code reviews and mentorship
- Track record of raising engineering standards
- Familiarity with financial market data and trading workflows
- Passion for innovation and continuous learning