Agentic AI Data Lead Software Engineer

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Category:
Software Engineering

Job Schedule:

Full time

Posted Date: T13:21:36+00:00

Job Shift:

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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 product ionize 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 JPMorgan

Chase within the Consumer & Community Banking Marketing Process Automation Team, you are 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 firm's business objectives.

Job responsibilities

* Lead, mentor, and grow a high-performing team of 5 - 7 engineers across multiple work streams, 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 platform's 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 platform's 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.

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