Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking - Data Technology, 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.

Job responsibilities

• Prioritized use cases by evaluating approved architecture standards, platform capabilities, and governance frameworks to scale onboarding on GenAI, ML, and Data platforms.
• Continuously participated in prototyping new technology to inform data technology teams about potential new tools for integration into existing data platforms.
• Partnered with customers, stakeholders, and product teams to understand business needs and translated them into technical details and implementation plans.
• Identified opportunities for automation and efficiencies, enabling a seamless customer experience and supporting GenAI, AI/ML, and Data initiatives.
• Monitored best practices and technology advancements in the industry and influenced their integration within the firm.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Extensive experience in AI/ML and GenAI solution design using different tools and techniques - GenAI frameworks, RAG architecture, Model Orchestration and Serving, model Experimentation etc.
• Experience working with data science, AI/ML product teams, working on projects covering the AI/ML and GenAI lifecycle.
• Comfortable presenting to Product Leadership, articulating team solutions, cross-functional dependencies, and risk exposures across technology, architecture, and data.
• Hands on experience in developing, debugging, and maintaining code in large-scale environments using modern programming languages (e.g., PySpark, Python)

Preferred qualifications, capabilities, and skills

• Master's degree (or equivalent experience) in Computer Science, Data Science, Engineering, or a related discipline.
• Experience working with snowflake, data bricks, feature platform.
• Knowledge of best practices of data management, cataloguing, lineage etc.