Drive innovation by designing and delivering enterprise-grade AI solutions that transform banking operations. Join a pioneering team at JPMorganChase where you can build autonomous agents to solve meaningful, complex challenges. You will collaborate with talented teams globally, bridging research and real-world engineering to deliver next-generation solutions. We value your expertise and support your growth through mentorship and mobility. Help shape how AI scales securely in a highly regulated environment.
As a Full Stack Engineer - ML Platform, Applied AI in the Doc AI team within Commercial and Investment Banking, you will design and deliver production architectures for AI-powered products and services. You will work at the intersection of software engineering and applied research to translate innovative ideas into scalable, enterprise-grade solutions. You will collaborate closely with cloud and site reliability engineering teams to build robust, secure systems. You will contribute to a team culture that values ownership, learning, and impact. Depending on your interests and experience, the role offers flexibility for an individual contributor path and optional people leadership opportunities.
Job Responsibilities
- Design and deliver enterprise-grade machine learning systems
- Implement distributed, multi-threaded, and scalable applications
- Build, test, and deploy highly secure automated pipelines for cloud systems, desktop applications, and ML solutions
- Apply software engineering and computer science best practices
- Develop and deploy business-critical, data-intensive applications
- Leverage foundational libraries and services for reuse across teams
- Utilize MLOps tools for versioning, reproducibility, and observability
- Collaborate with cloud and site reliability engineering teams to build robust production architectures
Required Qualifications, Capabilities, and Skills
- Degree in a quantitative discipline such as Computer Science, Mathematics, or Statistics
- Strong knowledge of and hands-on experience with Python
- Broad understanding of the software stack, including front end, back end, cloud architecture, messaging and queue systems, databases, security, and network configurations
- Experience with AWS and Kubernetes
- Ability to develop and deploy business-critical, data-intensive applications
- Strong understanding of computer science fundamentals and development best practices
- Ability to understand business objectives and align machine learning problem definitions accordingly
Preferred Qualifications, Capabilities, and Skills
- Experience in machine learning engineering roles
- Familiarity with higher-level interfaces such as Pydantic AI and Langraph
- Proficiency in TypeScript
- Experience mentoring others or leading teams
- Experience designing reusable libraries and services
- Interest in bridging scientific theory with enterprise-grade systems
- Passion for innovation and continuous learning
Why Join Us?
You will be part of a pioneering team that is transforming banking with AI.
The DocAI team is responsible for building, deploying, and maintaining advanced document processing models and platforms that support colleagues across the firm. The team is currently developing a next-generation AI platform and desktop application that enables users to automate document-centric workflows at enterprise scale, leveraging secure, agentic AI systems capable of processing hundreds of documents per second while operating within one of the world's most demanding and highly regulated environments.
We offer opportunities for career growth, mentorship, and the chance to work on impactful projects that shape the industry. Your expertise will help us build the next generation of AI solutions, making a difference for our clients and communities worldwide.
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