Senior Lead Software Engineer, Risk Management, Equities Technology - Prime Services

J.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. 

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 Senior Lead Software Engineer at JPMorganChase within the Corporate & Investment Bank (CIB), Equities Technology – Prime Services team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications—partnering closely with front-office stakeholders to improve trading and execution workflows.

Job Responsibilities

• Write high-quality Python code for front-office technology systems supporting Prime Services.
• Collaborate closely with Traders and Quantitative Researchers to deliver solutions that enhance trading and execution workflows.
• Create alignment with stakeholders, both technical and non-technical, to drive clarity on requirements, delivery approach, and outcomes.
• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors.
• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Develops secure and high-quality production code, and reviews and debugs code written by others.
• Drives decisions that influence product design, application functionality, and technical operations and processes.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
• 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.
• 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; leads communities of practice to drive awareness and use of new and leading-edge technologies.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 7+ years applied experience (or follow applicable local country guidance where required).
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Advanced proficiency in Python.
• In-depth knowledge across financial asset classes and their risk management concepts.
• Strong analytical, quantitative, and problem-solving skills.
• Ability to translate business and quant requirements into scalable target architectures and implementation roadmaps.
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) and setting 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.
• Ability to tackle design and functionality problems independently with little to no oversight.
• Practical cloud native experience.

Preferred qualifications, capabilities, and skills

• Prior experience with Athena / SecDB / Quartz / Beacon platforms 
• Data streaming knowledge on frameworks like Kafka and AMPS.