Lead Applied AI Engineer

Description

As a Senior Lead Applied AI Engineer 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