Lead Software Engineer - Front End/React/AIML

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 150,000 - 210,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Software Engineer within the AI/ML Data Platforms (AMDP) – Data Governance Engineering to spearhead the development and delivery of enterprise-scale data capabilities that drive firm-wide innovation.

You will own end-to-end software delivery for Java and Python services, batch jobs and data pipelines, apply CI/CD and security best practices, and collaborate with global teams across multiple time zones to ensure reliability and impact.

Qualifications

• 5+ years of experience with formal training or certification on software engineering concepts.
• Hands-on system design, application development, testing, and operational stability in production environments.
• Full stack development experience with Spring, Java, Python, Hibernate, Spark/PySpark, AWS cloud technologies, and Databricks.
• Experience with relational databases and SQL; familiarity with NoSQL databases and data modeling concepts.
• Ability to learn other coding languages and technologies as needed, with enthusiasm for continuous growth in both technical aptitude and business understanding.
• Knowledge across the data lifecycle including ingestion, validation, transformation, storage, governance and lineage considerations, and consumption patterns.
• Ability to develop, debug, and maintain code in large enterprise environments with established controls and standards.
• Familiarity with CI/CD, application resiliency, security best practices, and observability and monitoring.
• Hands-on experience using enterprise-authorized AI-assisted software development tools with demonstrated ability to critically evaluate and validate AI-generated outputs.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations.

Responsibilities

• Executes end-to-end software delivery for Java & Python based services, batch jobs, and data pipelines.
• Has strong proficiency in data processing, APIs services, scripting, and automation using common libraries and frameworks relevant to the role.
• Has familiarity with modern front-end technologies, especially in React.JS & Angular.
• Produces design artifacts for complex workflows covering pipeline orchestration, processing logic, dependency and failure handling, as well as in service-level objectives.
• Gathers, analyzes, and synthesizes data to produce reports, metrics, and visualizations that support business and operational insights.
• Identifies hidden problems and patterns in data and pipeline execution to drive system improvements.
• Works individually or as part of a distributed agile team to deliver projects on time with ownership and accountability.
• Contributes to engineering communities, improves internal libraries and utilities, and evaluates emerging technologies.

Skills

Spring

Java

Python

Hibernate

Spark/PySpark

AWS

Databricks

Job description

Join AIML Data Platforms to help shape the future of AI/ML by building enterprise-scale data platforms that drive innovation across the firm.

As Lead Software Engineer at JPMorganChase within the AI/ML Data Platforms (AMDP) - Data Governance Engineering team, you will spearhead the development and delivery of core Data capabilities as part of the AMDP platform that promote firm-wide innovation and excellence.

Job Responsibilities

• Executes end-to-end software delivery including design, development, testing, deployment, and technical troubleshooting for Java & Python based services, batch jobs, and data pipelines
• Has strongproficiencyin data processing, APIs services, scripting, and automation using common libraries and frameworks relevant to the role. Attention to performance, reliability, and testing discipline
• Has familiarity with modern front-end technologies, especially in React.JS & Angular
• Produces design artifacts for complex workflows covering pipeline orchestration, processing logic,dependencyand failure handling, as well as in service-level objectives
• Gathers, analyzes, and synthesizes data to produce reports, metrics, and visualizations that support business and operational insights
• Identifieshidden problems and patterns in data and pipeline execution — including data quality issues, drift, anomalies, and bottlenecks — to drive system improvements
• Works individually or as part of a distributed agile team to deliver projects on time with strong ownership and accountability. Flexibility to work with a global team and multiple time-zones
• Contribute to engineering communities, improve internal libraries and utilities, and evaluate emerging technologies where appropriate
• Leverages enterprise-authorized AI-assisted software development tools to improve code quality, delivery speed, and productivity, whilevalidatingoutputs through peer review, automated testing, and secure coding standards
• Applies knowledge of tools within the Software Development Life Cycle toolchain, Agilemethodologyand automation capabilities, to improve delivery speed and the value realized by automation

Required qualifications, capabilities, and skills

• 5+ years of experience with formal training or certificationonsoftware engineering concepts.
• Hands-on experience in system design, application development, testing, and operational stability in production environments
• Full stack development experience with Spring, Java, Python, Hibernate, Spark/PySpark, AWS cloud technologies, and Databricks
• Experience with relational databases and SQL; familiarity with NoSQL databases and data modeling concepts
• Ability to learn other coding languages and technologies as needed, with enthusiasm for continuous growth in both technical aptitude and business understanding
• Knowledge across the data lifecycle including ingestion, validation, transformation, storage, governance and lineage considerations, and consumption patterns
• Ability to develop, debug, andmaintaincode in large enterprise environments with established controls and standards
• Familiarity with continuous integration and delivery, application resiliency, security best practices, and observability and monitoring
• Hands-on experience using enterprise-authorized AI-assisted software development tools withdemonstratedability to critically evaluate andvalidateAI-generated outputs
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations

Preferred qualifications, capabilities, and skills

• AWS Solutions Architect/Developer or advanced-level certification.
• Proficiencyacross the data management lifecycle.
• Skilled in resolving code issues and proficient in Git for managing repositories and team collaboration.