Principal Software Engineer

If you are looking for a game-changing career, working for one of the world's leading financial institutions, you’ve come to the right place.

As a Principal Software Engineer at JPMorgan Chase within the Corporate Sector, you, you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various technologies to support one or more of the firm’s portfolios.

Job responsibilities

Architects and implements complex, scalable engineering frameworks and solutions using modern software design principles

Develops secure, high-quality production code for data-intensive applications and platforms, and reviews and mentors other engineers

Creates durable, reusable software frameworks and patterns that are leveraged across teams and functions

Designs and governs agentic AI systems, including multi-agent workflows, tool-use integrations, and human-in-the-loop controls appropriate for regulated financial services environments

Establishes engineering standards for LLM-based applications — RAG pipelines, embedding workflows, vector store integrations, and model serving — ensuring safety, observability, and reproducibility at scale

Drives adoption of advanced technical methods and practices aligned with the latest industry standards and product development methodologies

Serves as the function's go-to subject matter expert in one or more areas of focus within data engineering, platform architecture, or AI systems

Advises cross-functional teams on technological matters within your domain of expertise

Influences leaders and senior stakeholders across business, product, and technology teams on technical strategy and direction

Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.

Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation uired qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 7+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale

Hands-on experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures with tool use, memory, and multi-step reasoning in regulated environments

Expert in one or more programming languages, particularly Python and/or Java Advanced knowledge of software application development and technical processes, with considerable depth in one or more disciplines (e.g., cloud, AI/ML, data engineering)
Experience in large-scale data processing, microservices, API design, Kafka, Redis, Mem Cached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)
Advanced working knowledge of relational and No

SQL databases, vector stores, data lake architectures, and data governance

Practical cloud-native experience (AWS, Azure, or GCP)
Ability to present and effectively communicate with senior leaders and executives
Experience in Computer Science,…