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Job Description:

As a Lead Software Engineer at JPMorganChase within the Equities Derivatives Front Office Flow 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.

Job responsibilities

• Work with subject matter experts to develop solutions that meet business the business requirements.
• Develop Java services within a distributed hybrid-cloud system that supports end-to-end derivative product processing
• 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.

• Design and build AI agents and agentic pipelines to automate software development, testing, and operational workflows.

• Support integration of AI capabilities.

• Partner with front-office stakeholders to deliver scalable technology solutions for Equities Derivatives trading workflows.

• Build a stable, efficient, scalable cloud based solution which will be deployed globally.

• Design and code a significant amount of a robust, secure and efficient API to persist / retrieve data and implement the business logic
• Build JavaScript and C# front-end desktop applications to interface with the Java services
• Participation in code reviews and sharing of knowledge with other members of the team.
   

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (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 engineers on safe, compliant adoption within delivery practices
• Strong OO design skills with good knowledge of object modelling and design patterns
• Experience with development, deployment and maintenance of commercial service oriented application(s)
• Disciplined approach to code management, testing and deployment practices and high quality delivery
• Understanding of how to effectively utilize unit testing
• Great problem solving skills for problems with a mathematical/technological background
• Ability to work in a fast paced team oriented environment
• Ability to work effectively within a global team (spread across North America, EMEA, APAC etc.) while influencing and contributing towards the development of the global platform
• Experience of full project lifecycle, breaking requirements down into technical deliverables and effort estimation
   

• Knowledge of Java. Experience with AWS, Kubernetes, Docker or other Cloud technologies
• Business knowledge of simple derivative products (vanilla options, variance swaps, strategies involving vanillas): how these are used, how to price them, how to evaluate risk exposure using Greeks
• Exposure to NoSQL systems (Cassandra, MongoDB .etc.)
• Working knowledge of continuous integration and deployment processes