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Senior Lead Software Engineer - Front Office Trading
lead · Technology / Software Development
Build and support a mission-critical trade execution platform where your code directly impacts front office outcomes. You’ll work closely with Front Office and Middle Office users and help shape the tech roadmap across Python/Java, Kafka, AWS + Databricks, and SQL/NoSQL.
As a Senior Lead Software Engineer at JPMorgan Chase within Corporate Technology - Treasury & Chief Investment Office Technology team, we look first and foremost for people who are passionate around solving problems through innovation and engineering practices. You'll be required to apply your depth of knowledge and expertise to all aspects of the software development lifecycle, as well as partner continuously with your many stakeholders on a daily basis to stay focused on common goals. We embrace a culture of experimentation and constantly strive for improvement and learning. You’ll work in a collaborative, trusting, thought-provoking environment—one that encourages diversity of thought and creative solutions that are in the best interests of our engineers globally.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Develops secure high-quality production code, and reviews and debugs code written by others
- Manages responsibility for supporting the day-to-day operations of the trade execution platform, collaborating with Middle Office and Front Office business users.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
- 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
- Strong hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language and proficient in coding in one or more languages and frameworks such as Python, Pandas, Django or Java, Spring, MQ/Kafka
- Experience with AWS & Databricks ecosystem technology stacks as EMR, redshift, Dynamo DB, Athena, S3, Unity Catalog, Delta Lake, Spark etc.
- Experience with SQL and No-Sql Databases such as Oracle, MS Sql, PostgreSQL, Graph DB, Dynamo DB etc.
- Proficiency in automation and continuous delivery methods
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Practical cloud native experience and hands on experience in Cloud platforms like Kubernetes / Cloud Foundry
- 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, and skills
- Strong stakeholder management and the ability to align technical solutions with business goals.
- Familiarity with investment banking products - fixed income, derivatives
- Prior experience supporting trade execution platforms
- Hands-on experience with GenAI Developer Tooling