at J.P. Morgan
Bulge Bracket Investment BanksPosted a month ago
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**Lead Software Engineer - Regulatory Reporting** Lead a team focused on building, evolving, and supporting the Last Mile Reporting platform using AI, automation, and modern engineering tools. Design scalable solutions, improve platform reliability, and deliver trusted regulatory and financial reporting capabilities. **Key Responsibilities:** - Designs, builds, and improves platform architecture and infrastructure using AI-assisted engineering and automation. - Develops secure, high-quality production code in Python, Java, and related technologies. - Partners with stakeholders to evaluate architectural options, AI-enabled tools, data flows, controls, and integration patterns. - Leads adoption of new and emerging engineering practices, including AI-assisted development, prompt engineering, and agent building. - Promotes secure and responsible technology use and diversity, opportunity, inclusion, and respect. **Required Qualifications:** - 5+ years of relevant software engineering experience. - Demonstrated experience building and supporting regulatory and/or financial reporting applications in production environments. - Strong understanding of application, platform, and data architecture, including scalable infrastructure, integration patterns, reliability, resilience, and operational support. - Hands-on programming experience in Python, Java, or other mainstream programming languages. - Experience with AI prompt engineering, agent-based workflows, and automation techniques. **Preferred Qualifications:** - Experience with the Axiom ControllerView or similar regulatory reporting platforms. - Experience applying AI, machine learning, large language models, or agent frameworks to enterprise software engineering use cases. - Experience with financial services technology environments, regulatory change initiatives, audit/control processes, or enterprise reporting modernization. - Experience with Databricks or similar cloud-based data engineering and analytics platforms.
- Compensation
- Not specified
- City
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- Country
- United States
Currency: Not specified
Full Job Description
Location: Jersey City, NJ, United States
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 JPMorganChase within External Reporting and Financial Technology, you are an integral part of an agile team focused on using AI, automation, and modern engineering tools to build, evolve, and support the Last Mile Reporting platform architecture and infrastructure. As a core technical contributor, you will design scalable solutions, improve platform reliability, and help deliver trusted regulatory and financial reporting capabilities in a secure, stable, and efficient way.
Job responsibilities
Designs, builds, and improves Last Mile Reporting platform architecture and infrastructure using AI-assisted engineering, automation, and modern software development practices
Develops secure, high-quality production code in mainstream programming languages such as Python, Java, and related technologies, and reviews and debugs code written by others
Applies AI prompt engineering, agent-based workflows, and automation techniques to accelerate development, improve operational stability, and reduce recurring manual effort
Partners with technology, product, and reporting stakeholders to evaluate architectural options, AI-enabled tools, data flows, controls, and integration patterns for regulatory and financial reporting solutions
Leads adoption of new and emerging engineering practices, including AI-assisted development, prompt engineering, and agent building, while promoting secure and responsible technology use
Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
5+ years of relevant software engineering experience, including hands-on delivery and support of enterprise technology platforms
Demonstrated experience building and supporting regulatory and/or financial reporting applications in production environments
Strong understanding of application, platform, and data architecture, including scalable infrastructure, integration patterns, reliability, resiliency, and operational support
Hands-on programming experience in Python, Java, or other mainstream programming languages, with the ability to design, build, test, and maintain high-quality code
Hands-on practical experience delivering system design, application development, testing, deployment, monitoring, and operational stability for complex applications
Practical experience using AI tools to improve software engineering productivity, code quality, documentation, testing, and platform operations
Experience with AI prompt engineering, including the ability to create, refine, and evaluate prompts for engineering, documentation, analysis, and workflow automation use cases
Experience designing or building AI-enabled workflows, assistants, or agents that support development, data analysis, reporting, or operational processes
Strong understanding of cloud architecture and infrastructure, including AWS, Kubernetes, containerized deployment patterns, CI/CD, application resiliency, security, monitoring, and modern DevOps practices
Strong SQL and data analysis skills, with an understanding of data modeling, reporting data flows, data quality, reconciliations, and controls
Basic understanding of financial and regulatory concepts, including reporting requirements, controls, data lineage, and financial data interpretation
Preferred qualifications, capabilities, and skills
Hands-on experience with Axiom ControllerView or similar regulatory reporting platforms is a big plus
Experience applying AI, machine learning, large language models, or agent frameworks to enterprise software engineering, reporting, or operations use cases
Experience with financial services technology environments, regulatory change initiatives, audit/control processes, or enterprise reporting modernization
Experience with Databricks or similar cloud-based data engineering and analytics platforms
