Senior Lead Software Engineer: AI-Driven, Cloud-Native

JPMorganChase; Plano (TX); On-site; USD 150,000 - 230,000; Full time

Job summary

JPMorganChase in the United States seeks an experienced software engineer to join an agile team building trusted market-leading technology products in a secure, scalable way.

You will drive AI-enabled engineering practices, influence product design and technical operations, and collaborate with cross-functional teams to deliver high-quality production code and robust systems. This role emphasizes governance, risk management, and impactful business outcomes.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Experience developing or leading large or cross-functional teams of technologists.
• Expert-level backend engineering in Java (Spring Boot, Spring Integration, Hibernate/JPA) and/or Python; strong SQL and data modeling across relational and NoSQL systems.
• Deep AWS experience: ECS/EKS, Lambda, Aurora, DynamoDB, S3, Glue, CloudWatch — able to design, deploy, and operate cloud-native systems end-to-end.
• Hands-on Apache Kafka experience: topic design, consumer group management, exactly-once delivery, and stream processing patterns.
• Solid grasp of distributed systems fundamentals: consistency models, CAP trade-offs, idempotency, distributed transactions, and failure modes.
• Strong CI/CD and test engineering practice: you build the pipelines and write tests alongside the team.
• Excellent communicator — able to move fluidly between engineering teams and business/operations stakeholders in the same conversation.
• Experience leading multi-organization adoption of agentic AI-enabled engineering operating models (using enterprise-authorized tools within the work environment), including defining governance (human-in-the-loop decisioning, quality gates), measurement frameworks, and secure handling of sensitive inputs/outputs across teams.
• Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies.

Responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

Skills

Java

Spring Boot

Python

AWS

SQL/NoSQL

Kafka

CI/CD

Distributed Systems

Communication

AI governance

Tools

Spring Boot

Hibernate/JPA

ECS/EKS

Lambda

Aurora

DynamoDB

S3

Glue

CloudWatch

Kafka

Job description

JPMorganChase in the United States seeks an experienced software engineer to join an agile team building trusted market-leading technology products in a secure, scalable way.

You will drive AI-enabled engineering practices, influence product design and technical operations, and collaborate with cross-functional teams to deliver high-quality production code and robust systems. This role emphasizes governance, risk management, and impactful business outcomes.