As a Lead Software Engineer at JPMorganChase within Global Technology, you will lead and mentor an agile team to architect, design, and deliver trusted, market‐leading technology products in a secure, stable, and scalable way. In this role on the Rates Live Risk & PnL team, you will build and operate low‐latency, high‐availability Python applications used directly by Rates trading desks for intraday risk, PnL, and decision support in a quick‐paced front‐office environment.
Job Responsibilities
Lead the design and development of Python‐based live risk and PnL applications, driving continual, iterative improvements across product teams
Partner directly with Rates traders and stakeholders to translate business needs into reliable, low‐latency technical solutions
Drive decisions on software solutions, architecture, design, development, and technical troubleshooting with a focus on strategic direction and production excellence
Design and implement secure, high‐quality production code, with a strong focus on correctness, performance, and operational stability
Own architecture and design artifacts for complex, real‐time systems, ensuring non‐functional requirements (latency, throughput, availability) are met
Build and improve monitoring, alerting, and operational runbooks, and participate in production support/incident management as needed
Collaborate with DevOps and platform partners to improve CI/CD, deployment automation, and environment reliability
Mentor and coach junior and mid‐level engineers through code reviews, technical guidance, and best‐practice standards
Identify systemic issues (technical debt, performance bottlenecks, data quality gaps) and drive remediation aligned to long‐term platform goals
Influence and shape a team culture of diversity, opportunity, inclusion, and respect
Drive 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
Apply 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
Hands‐on experience in system design, application development, testing, and operational stability with a track record of leading complex technical initiatives
Advanced proficiency in Python, including building production services and performance-sensitive applications
Strong understanding of real‐time/distributed system concepts (e.g., concurrency, messaging/streaming patterns, caching, failure modes)
Experience delivering software in a large corporate environment with strong engineering standards (testing, code quality, security, SDLC)
Practical experience with CI/CD, application resiliency, and secure engineering, including production monitoring and incident response
Proven ability to lead technical design discussions, mentor engineers, and partner effectively with business stakeholders
Strong problem‐solving skills and ability to learn quickly and deliver high‐quality outcomes under time pressure
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
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
Preferred Qualifications, Capabilities, And Skills
Financial markets background (Rates products, risk, PnL, market data, trade lifecycle)
Exposure to Deephaven (or similar real‐time analytics/UI platforms) and its ecosystem, including installation/runtime dependencies (e.g., Java) and related operational considerations
Experience with DevOps practices for low‐latency services (deployments, observability, capacity/performance testing, environment management)
Understanding of UI programming (web or desktop) and collaborating across UI/backend boundaries to deliver trader‐facing workflows
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
J.P. Morgan is an equal opportunity employer and places a high value on diversity and inclusion. The company does 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. Reasonable accommodations are available for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
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📌 Lead Software Engineer, Global Technology (New South Wales)
🏢 Jpmorganchase
📍 New South Wales