Senior Principal Software Engineer - Cloud, Distributed Systems & Data Platforms
TypeFull-time job
LocationIndia
Posted3 hours ago
We’re looking for a tech leader ready to take their career to new heights. Join the ranks of top talent at one of the world’s most influential companies.
As a Senior 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
Sets strategy and operating standards for agentic AI-enabled engineering across a portfolio (using enterprise-authorized tools within the work environment) to drive measurable improvements in delivery speed, reliability, and code quality (e.g., AI-orchestrated SDLC/TLM automation, release readiness gating, incident triage/root-cause acceleration, and large-scale refactoring/test modernization), while defining guardrails for validation, security, resiliency, and reuse across teams and functions.
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 at scale.
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 on software engineering concepts and 10+ 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
Demonstrated experience designing and scaling agentic AI-enabled development patterns (using enterprise-authorized tools within the work environment) across teams/functions, including establishing governance for human-in-the-loop validation, traceability/auditability, and secure handling of sensitive inputs/outputs.
Strong understanding of responsible AI use and control expectations at scale, including security/resiliency implications, data sensitivity, and risk-based governance; ability to advise senior leaders on safe adoption, reuse, and measurable outcomes.
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
Originally posted on Himalayas
As a Senior 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
Sets strategy and operating standards for agentic AI-enabled engineering across a portfolio (using enterprise-authorized tools within the work environment) to drive measurable improvements in delivery speed, reliability, and code quality (e.g., AI-orchestrated SDLC/TLM automation, release readiness gating, incident triage/root-cause acceleration, and large-scale refactoring/test modernization), while defining guardrails for validation, security, resiliency, and reuse across teams and functions.
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 at scale.
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 on software engineering concepts and 10+ 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
Demonstrated experience designing and scaling agentic AI-enabled development patterns (using enterprise-authorized tools within the work environment) across teams/functions, including establishing governance for human-in-the-loop validation, traceability/auditability, and secure handling of sensitive inputs/outputs.
Strong understanding of responsible AI use and control expectations at scale, including security/resiliency implications, data sensitivity, and risk-based governance; ability to advise senior leaders on safe adoption, reuse, and measurable outcomes.
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
Originally posted on Himalayas
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