About this role
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. In this role, you’ll collaborate across technical teams to advance financial technologies and make a significant impact within the Chief Data & Analytics Office (CDAO), which leads the firm’s data and analytics journey by ensuring data quality, integrity, and security while harnessing AI and machine learning to promote insights, innovation, and commercial outcomes.
As a Senior Lead Software Engineer at JPMorgan Chase within the AIML Data Platforms - Chief Data & Analytics (CDAO)Team, you serve in a lead role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities.
Job responsibilities
- Provides technical leadership and strategic direction for AI/ML engineering teams developing enterprise AI solutions
- Drives the architecture and implementation of scalable machine learning platforms and data pipelines
- Ensures successful delivery of AI products leveraging generative AI, NLP, and other ML technologies
- Identifies and prioritizes AI/ML initiatives aligned with business objectives and industry trends
- Provides input on technology roadmaps, build-vs-buy decisions, and ML infrastructure investments
- Creates a culture of innovation, experimentation, and continuous learning in AI/ML practices
Required qualifications, capabilities, and skills
- Formal training in software engineering, data science, or related field with 5+ years experience
- Experience leading teams building production AI/ML systems at scale
- Proficiency in Java for both client-side and server-side application development
- Proficiency in HTML, CSS, and modern front-end web technologies
- Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices
- In-depth knowledge of the financial services industry and AI/ML applications in enterprise contexts
- Strong ability to communicate complex AI/ML concepts to technical and business stakeholders
Preferred qualifications, capabilities, and skills
- Experience working at code level
- Experience with Agile transformation initiatives
- Track record of building and scaling engineering teams
- Experience with cloud architecture and migration strategies