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Senior Lead Software Engineer - Java/Algo Trading
senior · Technology / Software Development
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Bank, specifically in the Markets Technology, Options Algorithmic trading sub-line of business, 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. Your technical prowess and problem-solving abilities will be put to use to tackle a variety of challenges across different technologies and applications.
As part of the Electronic Trading Technology (ETT) team, your responsibilities will include the development and upkeep of the robust technology infrastructure that underpins our electronic trading activities. This will involve the design and execution of systems for order management, trade execution, market data processing, and risk management. Within the ETT, you will be a member of the Options Algorithmic Trading team, focusing on the development and refinement of algorithmic trading engines specifically for options instruments, driving significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Execute creative software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- 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
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendor
- Collaborate with the product team to translate trading strategies into efficient and scalable algorithms
- Continuously improve and refactor existing codebases to enhance performance, implement comprehensive testing, and ensure the reliability of trading systems
- Design and implement algorithmic trading strategies, focusing on optimizing execution and performance in a low-touch trading environment
- Serves as a function-wide subject matter expert in one or more areas of focus and drives decisions influencing product designs, application functionality, and technical operations and processes
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
- Adds to the team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s) (i.e. Java - with strong understanding of data structures, algorithms, and multi threading in Java)
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
- Experience with algorithmic trading systems and familiarity with trading protocols such as FIX
- Practical experience with performance optimization and low-touch system design
- Familiarity with financial markets and trading concepts, particularly in equities and options
- Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Ability to tackle design and functionality problems independently with little to no oversight
- Practical cloud native experience
- Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
Preferred qualifications, capabilities, and skills
- Experience in designing and implementing high-performance, low-touch trading systems. Familiarity with financial data feeds and market data integration, ensuring efficient data handling and processing in trading systems.
- Ability to troubleshoot complex software issues and optimize application performance and reliability.
- Experience with messaging systems such as AMPS or Kafka, particularly in the context of real-time data streaming and processing.
- Experience with Cucumber for behavior-driven development (BDD) and testing, particularly in Java environments.
- Experience with automation tools and scripting languages (e.g., Python, Shell) to streamline testing and reporting.
- Proficiency in working with Linux operating systems, including scripting and basic administration tasks relevant to trading systems.
- Familiarity with monitoring and logging tools such as Grafana or Splunk for application performance and system health monitoring