This listing doesn't post a salary. Most similar roles pay
$174,600–$225,000.
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
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
As a Principal Software Engineer within the Corporate Sector, you will join an agile team to architect and implement complex, scalable engineering frameworks for data-intensive applications. You will develop high-quality production code, mentor other engineers, and create reusable software patterns across functions. A primary focus involves designing and governing agentic AI systems, including multi-agent workflows and RAG pipelines, while ensuring safety and observability in regulated financial environments. Your daily work involves building LLM-based applications, managing vector stores, and integrating tool-use capabilities. You will utilize Python or Java, Kafka, Redis, MemCached, and orchestration frameworks like Airflow or Temporal. Additionally, you will leverage cloud-native platforms such as AWS, Azure, or GCP, along with Spark, Databricks, and Snowflake to solve complex data engineering and platform architecture challenges within the financial services domain.
What does a Software Engineer earn?
Median $197500 from 2196 postings across 133 companies.
Architect and implement complex, scalable engineering frameworks using modern software design principles.
Develop secure, high-quality production code for data-intensive applications and mentor other engineers.
Create durable, reusable software patterns that are utilized across multiple teams and functions.
Design and govern agentic AI systems including multi-agent workflows and tool-use integrations for regulated environments.
Establish engineering standards for LLM-based applications, including RAG pipelines and vector store integrations.
Architect and govern AI-enabled engineering workflows to improve delivery speed, code quality, and operational outcomes.
Serve as a subject matter expert in data engineering, platform architecture, or AI systems.
Influence senior stakeholders on technical strategy and the adoption of advanced industry standards.
What we're looking for
Formal training or certification on software engineering concepts and 7+ years of applied experience.
Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field.
Hands-on experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures in regulated environments.
Expert knowledge in one or more programming languages, particularly Python and/or Java.
Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools, and orchestration frameworks.
Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance.
Practical cloud-native experience with AWS, Azure, or GCP.
Experience with LLM orchestration, model serving infrastructure, and big data technologies like Spark/PySpark (preferred).