Lead Software Engineer-AI Research, Development, and Innovation

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-AI Research, Development, and Innovation at JPMorgan Chase within the Corporate Sector's Cloud Foundational Services (CFS) team, you will be at the forefront of developing AI solutions through innovation, driving hands-on research & prototyping through AI assisted development, and engineering of advanced technologies that support strategic goals and new product incubation.

Your expertise will be essential in developing and testing innovative AI solutions, collaborating closely with senior leaders and peers to transform creative ideas into impactful technical implementations.

In addition to building cutting-edge AI solutions, you will champion the adoption of AI across RDI and CFS by coaching, mentoring, and sharing best practices, helping to elevate the organization's AI capabilities.

Your contributions will foster a dynamic and forward-thinking environment, positioning CFS as a leader in AI-driven development and adopting AI solutions first approach.

Job Responsibilities:


* AI-Driven Development & Prototyping: Champion the use of AI development assistants (e.g., Copilot, Claude, LLM Suite) to accelerate prototyping and deliver proof-of-value rapidly.

Apply a can-do attitude to solve business challenges with AI-powered solutions.


* Research and Development: Conduct hands-on research to explore emerging AI technologies, frameworks and approaches.

Develop innovative technical solutions that address the specific needs of Research, Development, and Innovation initiatives.


* Prototyping and Pilot Programs: Create and refine prototypes and pilot programs to demonstrate the viability and potential of new technologies or approaches.

Rapidly iterate on designs to improve functionality and performance.


* Engineering Excellence: Design and build robust, scalable, cloud-native platforms leveraging distributed systems and microservices.

Integrate and fine-tune LLMs, develop agentic AI architectures (Agent-to-Agent, MCP), and engineer prompt-driven workflows


* Documentation and Communication: Document technical specifications, designs, and best practices.

Communicate technical concepts effectively to both technical and non-technical audiences, ensuring clarity and understanding.


* Collaboration and Influence: Work collaboratively with peers, technology leaders, application/platform engineers, and architects.

Participate in major technical decisions, developing technical proposals that consider alternatives and business cases.


* Innovation Frameworks: Apply proven innovation frameworks to guide the development of new technologies and solutions.

Evaluate emerging technologies and recommend the best solutions for future state architecture.

Required qualifications, capabilities, and skills


* Formal training or certification on software engineering concepts and 5+ years appl...