Lead Software Engineer - Python, Data, Cloud, AIML

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Markets Research Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will work on challenging Cloud-native data, backend engineering and AIML engineering, helping us industrialize AI/ML models at Production scale. This role is a technical hands-on Engineering role. Experience with data science/ML modeling is advantageous but not essential to this role.

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with 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.

• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems

• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development

• Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps

• Designs and implements data engineering solutions, leveraging modern big data technologies

• Contributes to software engineering communities of practice and events that explore new and emerging technologies

• Embraces a passion for learning, problem-solving, creative thinking and a can-do attitude.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and proficient applied experience

• Hands-on practical experience in system design, application development, testing, and operational stability