Senior Principal Software Engineer TreasuryCIO Technology

Are you a seasoned engineer ready to solve complex high-impact problems at one of the worlds most influential financial institutions At JPMorganChase we invest in our engineers and give them the tools autonomy and scale to build technology that matters for millions of customers and the global economy.

As a Senior Principal Software Engineer at JPMorganChase within Corporate Technology you will serve as a technical authority driving the design and delivery of large-scale cloud-native systems that power critical business capabilities across the firm and specifically within Corporate Treasury. Corporate Treasury operates across a broad remit with responsibilities that include managing the firms structural interest rate risk and foreign exchange (FX) hedging strategy; executing debt issuance to support the firms funding needs; overseeing the Chief Investment Office (CIO) / investment portfolio; and developing and calculating Fund Transfer Pricing (FTP) to allocate internal funding and liquidity costs benefits and incentives across lines of business. You will influence engineering strategy set technical direction and partner with senior leaders and cross-functional teams to solve some of the most complex challenges in financial technology. Your work will directly shape how the firm builds scales and modernizes its technology landscape.

Job Responsibilities

• Architect and deliver highly scalable cloud-native solutions on AWS applying modern microservices and API-first design principles across enterprise platforms
• Define and champion engineering standards patterns and best practices for software development DevOps tooling and continuous delivery pipelines
• Lead technical design reviews and provide authoritative guidance on system architecture ensuring solutions meet performance reliability and security requirements
• Drive the adoption of modern DevOps practices including infrastructure as code CI/CD automation and observability frameworks across engineering teams
• Develop and maintain robust production-grade services using Python or equivalent modern programming languages with a focus on code quality and maintainability
• Collaborate with product architecture and business stakeholders to translate complex requirements into scalable technical solutions with measurable outcomes
• Identify and resolve systemic technical risks performance bottlenecks and architectural gaps across distributed systems
• Mentor and influence senior engineers across teams elevating technical craft and fostering a culture of engineering excellence
• Design build and deploy AI-enabled solutions to meet business needs

Required qualifications capabilities and skills

• Formal training or certification on software engineering concepts and 10 years applied experience
• Deep expertise in AWS cloud services including compute networking storage and managed services with hands-on experience designing and operating production workloads
• Proven experience building and scaling microservices architectures and RESTful or event-driven APIs in distributed high-availability environments
• Strong proficiency in Python or comparable modern programming languages with a demonstrated ability to write clean testable and maintainable code
• Proven experience designing building and deploying AI-enabled solutions to meet business needs.
• Extensive experience with modern DevOps practices and tooling including CI/CD pipelines infrastructure as code (e.g. Terraform CloudFormation) and container orchestration (e.g. Kubernetes Docker)
• Demonstrated ability to lead technical decision-making and influence engineering direction across large cross-functional teams
• Strong analytical and problem-solving skills with experience diagnosing and resolving complex issues in distributed systems at scale
• Excellent communication skills with the ability to present technical concepts clearly to both technical and non-technical audiences

Preferred qualifications capabilities and skills

• Experience applying artificial intelligence or machine learning techniques within enterprise software platforms or data-intensive applications
• Hands-on experience with big data technologies such as Apache Spark Kafka Hadoop or cloud-native data platforms (e.g. AWS EMR Glue or Redshift)
• Exposure to platform engineering or internal developer platform (IDP) initiatives at enterprise scale