Python Senior Lead Software Engineer- Fixed Income Systematic Portfolios

About the role

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Python Senior Lead Software Engineer in Fixed Income Systematic Portfolios at JPMorganChase within the Asset and Wealth Management team, you will drive significant business impact by applying deep technical expertise and problem-solving methodologies. You will fundamentally change how JPMorganChase Asset Management manages fixed income systematic portfolios, including account construction, optimization, and scaling. As a lead in Systematic Portfolio Management Technology, you'll partner with portfolio managers and quants to turn research into production systems that directly drive investment decisions. You'll build and evolve the platform powering portfolio optimization and performance insight, from data through to user experience, focusing on agentic flows to design intelligent, automated workflows.

Responsibilities

• Leads the design and delivery of core systematic portfolio tooling, translating quantitative research and portfolio needs into resilient production platforms.
• Partners with portfolio managers and quantitative researchers to build optimization, risk/exposure, and performance insight workflows that are clear and actionable for stakeholders.
• Drives agentic automated flows across the lifecycle from data to analytics to execution and controls, raising standards for reliability, scalability, and operational excellence.
• Provides technical guidance and direction to support the business, technical teams, contractors, and vendors.
• Develops secure and high-quality production code, and reviews and debugs code written by others.
• Drives adoption and governance of approved AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis). Establishes measurable validation standards (secure coding, peer review, automated testing) and promotes 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 value realized by automation at scale.
• Drives decisions influencing product design, application functionality, and technical operations and processes.
• Serves as a function-wide subject matter expert in one or more areas of focus.
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle.
• Influences peers and project decision-makers to consider the use and application of leading-edge technologies.

Requirements

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Advanced experience coding with Python.
• Ability to tackle design and functionality problems independently with little to no oversight, balancing speed, rigor, and risk.
• Practical cloud-native experience, including building, deploying, and operating services with strong observability and resilience.
• Experience with systematic investing or quantitative analytics workflows, including working with market/portfolio datasets and producing performance and risk insights for stakeholders.
• Familiarity with portfolio optimization concepts and tooling (e.g., commercial optimization solvers), ability to productionize research prototypes into scalable services, and working knowledge of interactive research and prototyping workflows (e.g., notebooks) and performance-focused compute patterns (parallel/asynchronous processing).
• Demonstrated experience leading effective use of enterprise-authorized 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 senior engineers/leads on compliant usage patterns and controls.
• Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field.

Preferred Qualifications

• Experience building systematic portfolio construction/optimization platforms in a front-office environment.
• Familiarity with optimization solvers and numerical methods (e.g., Gurobi, Axioma, MSCI Open Optimizer).
• Strong Python for analytics plus experience productionizing research workflows.
• Experience with Java, Kotlin, Clojure, or other functional languages.
• Experience integrating market data sources and building reliable analytics pipelines (e.g., Bloomberg/FactSet/MSCI).

Benefits

• Competitive total rewards package including base salary, commission-based pay, and/or discretionary incentive compensation (cash and/or forfeitable equity).
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

About the team

J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. The team is driven by innovators who create technology solutions to make the business work more efficiently and help clients get and remain properly invested. Agile technologists thrive in a cloud-native environment that values continuous learning using a data-centric approach in developing innovative technology solutions.