below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$150,000–$216,387.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
As a Sr. Lead Software Engineer: Backend Engineering within the Digital Technology, Personalization & Insights team, you will serve as a core technical contributor in an agile environment. You will develop secure, high-quality production code, review and debug peer code, and provide technical guidance to teams, contractors, and vendors. Your role involves driving decisions on product design, application functionality, and technical operations while advocating for firmwide frameworks and AI-assisted engineering practices. You will build high-throughput, low-latency applications deployed in AWS to power personalized experiences across banking channels. Required skills include proficiency in Object-Oriented languages like Java, C++, or Python, along with experience in microservices, Kafka, Kinesis, Flink, Redis, Ray, Spark, Docker, Kubernetes, and Airflow. You must also demonstrate expertise in CI/CD, application resiliency, and security.
Develop secure, high-quality production code and perform code reviews and debugging for other team members.
Provide technical guidance and direction to business teams, contractors, and external vendors.
Drive decisions regarding product design, application functionality, and technical operations.
Serve as a subject matter expert in specific technical areas to support business objectives.
Advocate for firmwide frameworks, tools, and Software Development Life Cycle practices.
Drive the adoption and governance of AI-assisted engineering practices to improve code quality and delivery speed.
Apply SDLC toolchain knowledge to improve the value of automation at scale.
Coach engineers on the responsible and compliant use of AI tools in engineering workflows.
What we're looking for
Formal training or certification on software engineering concepts and 5+ years of applied experience.
Hands-on software development experience in an Object-Oriented programming language such as Java, C++, or Python.
Depth of knowledge and experience in three of the following: high-throughput microservices on AWS, real-time stream processing, caching systems, or large volume data processing.
Solid fundamentals and experience in containers (Docker), container orchestration (Kubernetes, ECS), and DAG orchestration (Airflow, Kubeflow).
Solid understanding of agile methodologies and knowledge of SDLC including CI/CD, Application Resiliency, and Security.
Demonstrated experience leading the use of enterprise-authorized AI-assisted software development tools and setting expectations for validating AI outputs.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and coaching others on compliant usage.
Experience with recommendation and personalization systems (preferred).