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Job description
If you are looking for a game-changing career, working for one of the world's leading financial institutions, you’ve come to the right place.
As a Principal Software Engineer at JPMorganChase within the Asset & Wealth Management, Derivatives Team, you, you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various technologies to support one or more of the firm’s portfolios.
J.P. Morgan Asset Management is seeking an Executive Director to lead the architecture, engineering, and delivery of its strategic derivatives platform on the Athena (Python) framework. This is a hands-on technical leadership role requiring deep expertise in platform design, architecture, and large-scale engineering execution. The successful candidate will define the platform vision, set engineering standards, drive a multi-year roadmap, and ensure capabilities support the needs of Portfolio Managers across Fixed Income, Equity, and Multi-Asset strategies. They will make key technical decisions, solve complex engineering challenges, and provide hands‑on guidance to senior engineers and technical leads. The role also includes leading and developing multiple engineering teams while fostering a culture of engineering excellence, technical rigor, and continuous improvement.
Job responsibilities
You will manage senior relationships spanning Portfolio Management, Trading, Operations, and Accounting — communicating with authority and clarity on architecture decisions, delivery status, and platform capability.
Develops secure and high‑quality production code, and reviews and debugs code written by others
Architects and governs agentic AI‑enabled engineering workflows (using enterprise‑authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI‑driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root‑cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.
Applies 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 at scale.
Advises cross‑functional teams on technological matters within domain of expertise
Serves as the function’s go‑to subject matter expert
Contributes to the development of technical methods in specialized fields in line with the latest product development methodologies
Creates durable, reusable software frameworks that are leveraged across teams and functions
Influences leaders and senior stakeholders across business, product, and technology teams
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 10+ years applied experience
Proven experience as a quant developer, with a strong history of close collaboration with quants, traders, or portfolio managers in a front‑office or investment technology context
Deep knowledge of derivatives trade lifecycle, and Fixed Income and/or Equity Derivatives
Deep understanding of the pricing, risk, and analytics of financial products, including the systems and data models that support them
Strong technical proficiency in Python, with working knowledge of Java, C++, or C#
Experience in the JPMorganChase Athena platform is a strong plus; experience in comparable industry platforms such as Quartz or Beacon is also highly valued for candidates without Athena knowledge
Executive presence with the ability to communicate complex technical concepts authoritatively to both technical and non‑technical audiences
Demonstrated experience designing and leading adoption of agentic AI‑enabled development practices (using enterprise‑authorized tools within the work environment) across teams, including setting standards for human‑in‑the‑loop validation, auditability/traceability of changes, and secure handling of sensitive data.
Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk‑based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.
Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplines
Preferred qualifications, capabilities, and skills
Understanding of the business
Practical cloud native experience
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Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.