We have an exciting opportunity for you to lead the design and delivery of high-impact analytics and AI systems at scale. Join us to drive innovation, reliability, and performance in a cloud-native environment.

As a Principal Software Engineer at JPMorgan Chase within the Corporate technology team, you architect and deliver core components of a distributed data platform.. You partner with product, data, SRE, and security teams to achieve reliability, performance, and compliance at scale. You help shape engineering standards and drive technical excellence across the team.

Job responsibilities

• Architect end-to-end platform components for streaming, batch, and interactive workloads
• Write high-quality, performant code and build robust APIs and services
• Implement resilient distributed workflows and optimize compute clusters and storage layers
• Embed security, governance, and compliance controls in services and pipelines
• Define SLIs/SLOs, automate alerts, and contribute to reliability and operations
• Mentor senior engineers and champion engineering excellence and risk controls

Required qualifications, capabilities and skills

• Formal training or certification in software engineering and 12+ years applied experience
• Demonstrable ownership of cloud-native distributed systems or data platforms at scale
• Deep expertise in at least two areas: cloud platforms, storage/lakehouse tech, data processing/streaming, query/compute engines, distributed systems, security/governance, DevOps/SRE
• Hands-on practical experience in system design, application development, testing, and operational stability
• Proficient in coding in Java, Scala, Python, or Go
• Experience in developing, debugging, and maintaining code in large corporate environments
• Excellent system design and communication skills; ability to influence roadmaps and standards across teams

Preferred qualifications, capabilities and skills

• Experience in regulated or mission-critical environments with strict RTO/RPO requirements
• Hands-on with data governance stacks, data quality frameworks, and policy engines
• Familiarity with ML/AI data patterns and low-latency serving
• Graduate degree in CS/Engineering or equivalent