Lead Software Engineer - Java, Python, AWS

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

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 Corporate and Investment Banking (CIB) Payments Technology team, you play a crucial role in an agile team that is dedicated to improving, creating, and delivering trusted market-leading technology products in a secure, stable, and scalable manner. As a key technical contributor, you are tasked with implementing vital technology solutions across numerous technical areas within various business functions to support the firm's business goals.

As a Regulatory Reporting Lead engineer, you will be accountable for end-to-end technical delivery across Regulatory initiatives. You will also help shape how the team applies modern data platforms (Databricks, Spark) and AI-assisted engineering to reporting workloads.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Build and optimize large-scale data and reporting pipelines on Databricks/Spark, including data quality, lineage, and reconciliation controls for regulatory submissions
• Applies AI and machine-learning techniques and AI-assisted engineering tools to accelerate delivery and automate reporting and remediation workflows
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Closely work with external vendors, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation

Required qualifications, capabilities, and skills

• Bachelor’s Degree in Computer Science, Cybersecurity, Data Science, or related disciplines
• Formal training or certification on engineering concepts and 5+ years of experience in system engineering or software development.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Proficient in coding using the following technology stack: Java, Junit, Maven, Hibernate, Spring Boot, Spring JPA, Spring Batch
• Hands-on experience with Databricks and/or Apache Spark for batch data processing — Delta Lake, Spark SQL, PySpark or Spark with Java/Scala, and job orchestration
• Strong programming experience in Python for data engineering, automation, and scripting
• Familiarity with one or more DBMS like Oracle, MySQL, or others
• Proficient in all aspects of the Software Development Life Cycle
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Advanced understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security and proficient in automation and continuous delivery methods

Preferred qualifications, capabilities, and skills

• Previous working experience with Payment technology, and/or Reg Reporting tech will be a plus
• In-depth knowledge of the financial services industry (payment products preferred) and related regulatory landscape and their IT systems
• Experience applying AI/ML models or large language models (LLMs) to data pipelines, reconciliation, or anomaly detection
• Exposure to cloud technologies, Splunk, Apache Kafka, Grafana