Lead Software Engineer - Regulatory Reporting

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorganChase in Jersey City is seeking a Lead Software Engineer to shape the Last Mile Reporting platform architecture and infrastructure. You will contribute as a core technical member, building scalable solutions and ensuring secure, reliable regulatory and financial reporting capabilities.

The role emphasizes AI-assisted development, prompt engineering, and automation while collaborating with stakeholders across technology, product, and reporting.

Qualifications

• 5+ years of relevant software engineering experience in enterprise technology platforms.
• Experience building/regulatory/financial reporting applications in production.
• Strong understanding of cloud architecture, scalable infra, and data workflows.
• Hands-on programming in Python/Java, with quality code delivery.
• Experience delivering complex app design, development, testing, deployment, monitoring, and operation.
• Practical use of AI tools to improve software engineering productivity and reliability.
• Experience with AI prompt engineering for engineering/documentation workflows.
• Knowledge of AI-enabled workflows and agent frameworks for reporting processes.
• Cloud-native patterns with AWS, Kubernetes, CI/CD, security, and monitoring.
• Strong SQL and data analysis, data modeling, and data quality controls.
• Basic understanding of financial and regulatory concepts, reporting requirements, and data lineage.

Responsibilities

• Designs and evolves Last Mile Reporting platform architecture and infrastructure using AI-enabled engineering and automation.
• Develops secure, high-quality production code in Python, Java, and related technologies; reviews colleagues' code.
• Applies AI prompt engineering and automation to accelerate development and improve stability.
• Partners with tech, product, and reporting stakeholders to evaluate architectural options for regulatory and financial reporting solutions.
• Leads adoption of new engineering practices including AI-assisted development and secure tech use.
• Contributes to a team culture of diversity, opportunity, inclusion, and respect.

Skills

Python

Java

AWS

Kubernetes

CI/CD

AI tools

Data analysis

SQL

Tools

Databricks

Axiom ControllerView

Job 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 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