Python Lead Software Engineer

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