Job Description

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 Commercial & Investment Bank, 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.

Job responsibilities

• Leads the vision, strategy, design, and execution of derivatives migration for the Credit Business, driving adoption of the strategic technology platform
• Builds and continuously refines the product roadmap, providing end-to-end solutions and gaining efficiencies by bringing cross-functional teams together
• Drives delivery and execution as the product subject matter expert with an overall view of demand, resourcing, and project deliverables
• Establishes the operating model, owns end-to-end user relationships, and provides complete transparency to all stakeholders including senior trading, operations, and product control partners
• Manages interdependencies between strategic execution and the regulatory book of work for Securities & Derivatives, interpreting regulations and audit action points to define required work
• Traverses global teams across EMEA, NA, and ASIA, clearing program blockers and communicating effectively to drive alignment

• 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.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience

• Experience in hands-on development experience in technology project/program in a front-office capacity. Formal training or certification Computer Science, Mathematics, or a related technical discipline

• Proven experience managing programs requiring collaboration across various teams, stakeholders, and global regions

• Demonstrated expertise in delivery and execution of regulatory programs with strict timelines

• Strong experience tracking risk and dependencies, managing decision logs, monitoring issues, and investing time in retrospectives

• Advanced knowledge of trade lifecycle processes including clearing, compressions, book creations, and industry initiatives

• Experience creating UAT test plans, managing test cycles, and creating run books for major deliverables

• Ability to tackle design and functionality problems independently with little to no oversight

• 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.

Preferred qualifications, capabilities

• Credit Derivatives subject matter expertise or equivalent expertise in another complex asset class

• Hands-on experience with Python-based platforms or quantitative technology environments

• Experience with cross-asset risk, pricing, or trade management platforms (e.g., Athena or similar)

• Curiosity to deepen understanding of Credit business products and electronic/algorithmic trading workflows