JPMorgan Chase
From JPMorgan Chase's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
Here, you'll grow alongside talented engineers, collaborate across disciplines, and help define what's possible.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. At JPMorganChase, we build technology that matters — solutions that empower our risk managers, protect the firm, and shape the future of financial services. Joining our Market Risk Technology team means working at the intersection of engineering excellence and real-world financial impact, where your contributions are visible, valued, and meaningful. Here, you'll grow alongside talented engineers, collaborate across disciplines, and help define what's possible.
As a Lead Software Engineer (Vice President) at JPMorganChase within the Market Risk Technology 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. Our team develops the firm's strategic calculation, time series, and scenario management platforms for Firmwide Market Risk — integrating with front-office risk management systems to give risk managers the capability to assess the financial impact of adverse market scenarios at a firm-wide level.
Job responsibilities
Interface closely with business stakeholders, quantitative research analysts, and upstream and downstream technology teams across the firm to deliver well-integrated, high-quality solutions
Execute creative software solutions across design, development, and technical troubleshooting, thinking beyond conventional approaches to break down complex technical problems
Develop secure, high-quality production code while reviewing and debugging code written by others to maintain engineering excellence
Identify opportunities to eliminate or automate remediation of recurring issues to improve the overall operational stability of software applications and systems
Lead Python service and API design and delivery for risk workflows, ensuring scalability, reliability, and alignment with architectural standards
Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented assessment of architectural designs, technical credentials, and applicability within existing systems
Drives 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
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
Build AI-enhanced user features — including search, summarization, and explanation capabilities — with a human-in-the-loop approach to ensure correctness, security, and compliance
Foster a team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and advanced applied experience
Advanced development experience in Python, Java, or another object-oriented programming language
Hands-on practical experience delivering system design, application development, testing, and operational stability
Proficient in all aspects of the Software Development Life Cycle, including automation and continuous delivery methods
Advanced understanding of agile methodologies, including continuous integration and delivery, application resiliency, and security practices
Demonstrated proficiency in software applications and technical processes within a technical discipline such as cloud, artificial intelligence, or machine learning
In-depth knowledge of the financial services industry and its technology systems
Practical cloud-native development experience
Experience communicating effectively with both business-facing customers and technical teams
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
Familiarity with modern front-end technologies and UI development patterns
Familiarity with large language model application patterns, including embeddings, retrieval-augmented generation, evaluation frameworks, and guardrails, with experience productizing AI features
Experience working in financial services or risk technology environments
Exposure to market risk concepts such as Value at Risk, stress testing, or scenario analysis
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