Lead Software Engineer, AI/ML Data Governance

Salary: $61,000 - 101,000 per year Requirements:

• At least 5 years of experience, supported by formal training or certification in software engineering concepts.
• Hands-on experience in system design, application development, testing, and maintaining operational stability in production environments.
• Full-stack development experience with Spring, Java, Python, Hibernate, Spark or PySpark, AWS cloud technologies, and Databricks.
• Experience with relational databases and SQL, plus familiarity with NoSQL databases and data modeling.
• Ability and enthusiasm to learn additional programming languages and technologies while growing technical skills and business understanding.
• Knowledge of the data lifecycle, including ingestion, validation, transformation, storage, governance, lineage, and consumption.
• Ability to develop, debug, and maintain code in large enterprise environments with established controls and standards.
• Familiarity with continuous integration and delivery, application resiliency, security best practices, observability, and monitoring.
• Hands-on experience with enterprise-authorized AI-assisted software development tools, including the ability to critically assess and validate generated outputs.
• Understanding of responsible AI use in engineering, including data sensitivity, secure handling of inputs and outputs, and security and resiliency expectations.
• Proficiency in data processing, APIs, scripting, and automation using relevant libraries and frameworks, with attention to performance, reliability, and testing.
• Familiarity with modern front-end technologies, particularly React.js and Angular.
• Preferred: AWS Solutions Architect, AWS Developer, or advanced-level certification.
• Preferred: Proficiency across the data management lifecycle.
• Preferred: Skill in resolving code issues and experience with Git for repository management and team collaboration.

• Deliver software end to end—including design, development, testing, deployment, and technical troubleshooting—for Java- and Python-based services, batch jobs, and data pipelines.
• Create design artifacts for complex workflows, covering pipeline orchestration, processing logic, dependencies, failure handling, and service-level objectives.
• Gather, analyze, and synthesize data to produce reports, metrics, and visualizations that inform business and operational decisions.
• Detect data and pipeline issues, including quality problems, drift, anomalies, and bottlenecks, and use findings to improve systems.
• Deliver projects on time, working independently or within a distributed agile team and demonstrating ownership and accountability across global teams and time zones.
• Contribute to engineering communities, improve internal libraries and utilities, and assess emerging technologies where appropriate.
• Use enterprise-authorized AI-assisted development tools to improve code quality, delivery speed, and productivity, validating results through peer review, automated testing, and secure coding practices.
• Apply software development lifecycle tools, agile methods, and automation capabilities to accelerate delivery and increase the value of automation.

• AI
• AWS
• Angular
• Architect
• Cloud
• Databricks
• Git
• Hibernate
• Java
• Machine Learning
• NoSQL
• Python
• PySpark
• React
• SQL
• Security
• Spark
• Spring
• Support

More:

We are collaborating with hackajob to connect exceptional professionals with J.P. Morgan for this Lead Software Engineer role. Within JPMorganChases AI/ML Data Platforms (AMDP), youll join the Data Governance Engineering team and help shape the future of AI and machine learning by building enterprise-scale data platforms. As part of an agile team, youll help enhance, design, and deliver core data capabilities and software components for firm-wide innovation, with a focus on secure, stable, and scalable technology.

last updated 42 week of 2026