Location: New York, NY, United States

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking in the Data Technology organization, you are an integral part of an agile team dedicated to enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. Your role involves promoting significant business impact through your capabilities and contributions, utilizing deep technical expertise and problem-solving methodologies to address a diverse array of challenges across multiple technologies and applications. As the Senior Lead Solutions Engineer, you will actively promote the adoption of AI/ML & GenAI platforms and Data Products, ensuring standardized governance around AI and Data Lifecycle. You will collaborate with product, architecture, and platform teams to develop solutions for business use cases that support platform adoption.

Job Responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Create solution prioritized use cases by evaluating approved architecture standards, platform capabilities and governance frameworks to scale the onboarding on the GenAI, ML and Data platforms. 
• Develop blueprints or templates for efficient and automated customers onboarding to the platform for a quicker path to production. 
• Participate in continuous prototyping of new technology to inform data technology teams on potential new tools to be integrated as part of the existing platforms. 
• Partner with platform engineering and architecture to help evaluate the platform capabilities keeping performance, ease of use, integration, resilience and maintainability in mind.  
• Manage a team of Data and ML Solutions Engineer to ensure the highest quality of code, processes, demos and solutions by participating in hands on design discussions, peer reviews and troubleshooting. 

Required qualifications, capabilities and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Extensive experience in AI/ML solution design, and large-scale data transformation programs within complex, highly regulated environments. 
• Demonstrated success building both batch and real-time ML pipelines—including model training, serving, and monitoring—and automating workflows with orchestration tools (Airflow, Step Functions). 
• Strong understanding of Data Lake, relational and NoSQL databases, Data Governance frameworks, AI Ethics, Model Governance, Data Privacy. 
• Hands on experience in developing, debugging, and maintaining code in large-scale environments using modern programming languages (e.g., PySpark, Python) 
• Exceptional communication and stakeholder-management skills, to serve as a subject matter expert for various advanced data and ML solutions.

Preferred qualifications, capabilities and skills

• Master’s degree (or equivalent experience) in Computer Science, Data Science, Engineering, or a related discipline. 
• Knowledge of AI Ethics, Model Governance, MLOps, LLMOps process and best practices