Agentic AI Data Lead Software Engineer

Join our team as a Lead Data Products Software Engineer responsible for architecting building and scaling the Data Products Framework a next-generation platform that enables users to discover design build and productionize governed data products at enterprise scale. You will lead a team of engineers driving the technical strategy and execution of a platform that orchestrates the end-to-end data product lifecycle leveraging AI/Agentic AI policy-based governance and cloud-native architectures on AWS.

As a Lead Software Engineer at JPMorganChase within the Consumer & Community Banking Marketing Process Automation Team youare an integral part of an agile team that works to enhance build and deliver trusted market-leading technology products in a secure stable and scalable way. As a core technical contributor you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives.

Job responsibilities

• Lead mentor and grow a high-performing team of 5 7 engineers across multiple workstreams fostering a culture of innovation ownership and technical excellence.
• Set the technical vision and engineering roadmap for the Data Products platform aligning with firmwide priorities.
• Drive cross-functional collaboration with platform teams domain Data Product Owners AI/ML teams and governance teams.
• Architect and own the end-to-end technical design of the Data Products Studio a scalable enterprise-grade platform that orchestrates the discovery design build and productionization of data products from the CCB Data Lake and Snowflake.
• Design the platforms AI/Agentic AI layer leveraging intent agents NLP Text-to-SQL Knowledge Graphs (KAG) RAG Vector Databases and Agent-to-Agent (A2A) communication to enable intelligent automated data product creation and natural language interaction with the data estate.
• Define the platforms integration architecture with various firmwide systems as appropriate.
• Establish and enforce architectural standards design patterns and engineering best practices across the team ensuring scalability security resilience and maintainability.
• Lead the design and development of Agentic AI capabilities that power the Data Products Framework including autonomous discovery agents that profile and recommend data product candidates design agents that auto-generate data contracts and schema recommendations build agents that generate and optimize data pipelines governance agents that auto-apply entitlements based on data classification and quality agents that detect anomalies drift and trigger self-healing remediation.
• Architect the Agent-to-Agent communication layer enabling multi-agent orchestration across the data product lifecycle from discovery through productionization.
• Leverage RAG (Retrieval Augmented Generation) and Vector Databases to enable contextual knowledge-grounded AI interactions with metadata lineage and data catalog information.
• Implement NLP Text-to-SQL capabilities allowing business users to explore the CCB Data Lake and Snowflake using natural language lowering the barrier to data product discovery.

Required qualifications capabilities and skills

• Formal training or certification on software engineering concepts and 5 years applied experience
• 10 years of progressive experience in software engineering data engineering or platform engineering
• Strong leadership experience in guiding and mentoring varying levels of Software Engineers
• Proven track record of architecting and delivering large-scale enterprise-grade data platforms or frameworks from concept through production in a large corporate environment
• Deep hands-on expertise in Python SQL and at least one additional language (preferably Java 17 Spring Boot) with strong system design and distributed systems knowledge
• Extensive experience designing building and optimizing ETL/ELT pipelines at scale including batch and real-time data processing.
• Strong proficiency in PySpark for distributed data processing including DataFrame and Dataset APIs and Spark SQL.
• Experience working with UI frameworks (React Angular) will be an added advantage.
• Extensive experience with AWS cloud services including S3 Athena Glue Lambda Step Functions IAM KMS and Terraform.
• Basic knowledge of Snowflake (architecture performance optimization Tasks Streams Stored Procedures Materialized Views security model) is preferred but not mandatory.

• Deep understanding of data governance principles including metadata management data lineage access control (RBAC/ABAC) data classification and policy enforcement.

• Experience with Grafana or equivalent observability platforms for custom dashboards APM SLA monitoring and alerting is a plus
• Experience working with UI frameworks (React Angular) will be an added advantage