We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank - Digital & Platform Services, you play a crucial role in an agile team dedicated to improving, developing, and providing reliable, cutting-edge technology solutions that are secure, stable, and scalable. Job responsibilities Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors Develops secure and high-quality production code, and reviews and debugs code written by others Drives decisions that influence the product design, application functionality, and technical operations and processes Serves as a function-wide subject matter expert in one or more areas of focus 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, equity, inclusion, and respect Leads GenAI strategy and adoption: Spearheads generative AI initiatives, including chatbots and agentic architectures, aligned with business goals.

Collaborates cross-functionally: Integrates ML solutions with data scientists, engineers, and stakeholders to enhance platform capabilities.

Establishes ML lifecycle best practices: Develops standards for model development, deployment, monitoring, and maintenance.

Mentors ML engineering team: Guides and develops the team, fostering continuous learning and innovation.

Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience

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

Advanced in one or more programming language(s)

Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (., cloud, artificial intelligence, machine learning, mobile, 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 Proven leadership in ML projects: Demonstrated ability to lead machine learning initiatives and drive strategic AI adoption.

Expertise in GenAI technologies: In-depth knowledge of generative AI, LangChain, LangGraph, Autogen and other orchestration frameworks.

Strong knowledge of MLFlow

Solid understanding of system design and enterprise architecture patterns

Preferred capabilities and skills  Experience in payments: Prior experience working in the financial services industry, particularly in payments or banking, with an understanding of industry-specific challenges and opportunities.

GenAI Implementation Experience: Hands-on experience in implementing Generative AI solutions, such as chatbots or agentic architectures, in a production environment.

Advanced Data Analytics Skills: Proficiency in advanced data analytics and statistical methods, with the ability to derive actionable insights from complex datasets.

Certification in AI/ML: Relevant certifications in AI or ML, such as AWS Certified Machine Learning Specialty, Google Professional Machine Learning Engineer, or similar credentials, demonstrating a commitment to professional development in the field.