What are the responsibilities and job description for the Applied AI Engineer-Vice President position at JPMorgan Chase?
As Applied AI Engineer-Vice President at JPMorganChase within the Consumer & Community Banking Machine Learning, 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. Drive 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
- 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
- Drive innovation in machine learning solutions, ensuring scalability, flexibility, and future-proof architecture
- Act as a thought leader and trusted advisor to executive leadership, providing strategic recommendations on machine learning initiatives and solutions
- Architect and oversee the development of next-generation machine learning models and systems leveraging cutting-edge technologies
- Ensure the platform supports complex use cases, including real-time predictions, big data processing, and advanced analytics
- Promote software and model quality, integrity, and security across the organization
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5 years applied AI experience
- Proven track record of building and scaling software and or machine learning platforms in high-growth or enterprise environments
- 10 plus years of hands-on experience and expertise in software development frameworks and tools such as Java, Python and JavaScript
- Deep understanding of distributed systems, cloud-native architectures, and modern machine learning technologies
- Experience in cloud platforms such as AWS, GCP, or Azure
- Knowledgeable in machine learning frameworks, ML Ops tools and practices
- Strong proficiency in engineering programming languages (e.g., Python, Java) and infrastructure as code (e.g., Terraform, CloudFormation)
- Proficient in building AI Agents (e.g., LangChain, LangGraph, AutoGen), integration of tools (e.g., API) and RAG based solutions (e.g., open search)
- Hands-on experience with software development pipeline and orchestration tools (e.g., Jenkins, GitLab CI/CD)
- Exceptional ability to communicate complex technical concepts to both technical and non-technical audiences
- Hands-on experience with big data, pipeline, orchestration tools and real-time processing frameworks
Preferred qualifications, capabilities, and skills
- Certified as AWS Solutions Architect, Certified Developer, or similar certification