Lead Software Engineer - Java/Python/AI-ML

Overview

As a Lead Software Engineer in JPMorganChase’s Corporate Global Tax Technology team, you will shape cloud-based solutions that are secure, scalable, and trusted. You’ll work in an agile environment with architects and engineers to align tech with business goals and deliver impactful products. You’ll drive performance, security, and reliability while staying ahead of cloud and AI/ML trends to foster innovation. You’ll lead communities of practice and promote AI-assisted engineering practices to improve code quality and delivery speed. This is a chance to influence engineering culture and build high-impact tax tech platforms at scale.

Responsibilities

• Design, develop, and implement cloud-based applications and services
• Collaborate with architects and engineers to align solutions with business goals
• Optimize performance, scalability, and security of applications
• Participate in code reviews and provide constructive feedback
• Stay updated on Cloud and AI/ML technologies to drive innovation
• Lead communities of practice across Software Engineering for adoption of new tech
• Drive adoption of AI-assisted engineering practices to improve code quality and delivery
• Develop secure, high-quality production code and review others’ code
• Identify opportunities to automate recurring issues to improve operational stability
• Utilize SDLC tools and AI-assisted development to enhance automation and value

• Formal training or certification on software engineering concepts and applied experience
• Experienced in cloud development (AWS) with focus on application design and development
• Experience with AI/ML model integration, Prompt engineering, LLM APIs (OpenAI, Bedrock) and Generative AI
• Advanced in Java and Python
• Strong experience with cloud platforms (AWS, Azure, or Google Cloud)
• Experience building RESTful APIs and event-driven/serverless architectures
• Proven track record leading use of approved AI-assisted software development tools and setting team expectations for AI outputs
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies (CI/CD, Application Resiliency, Security)
• Experience in Infrastructure as code (Terraform or equivalent)

• leadership
• collaboration
• communication
• AWS
• Azure
• Google Cloud Platform