Develop and maintain reliable, secure software and distributed services for financial applications. Responsibilities include system design, Python API development, CI/CD automation, cloud infrastructure support, observability, incident response, root cause analysis, and reliability improvements. The role collaborates with engineering and production support teams, analyzes operational data, uses authorized AI tools, and participates in technical communities.
Play a key role in ensuring system reliability at one of the world’s most iconic and largest financial institutions.
As a Site Reliability Engineer II at JPMorgan Chase within Asset and Wealth Management, you will use technology to solve business problems and leverage software engineering best practices as we strive towards excellence. This role often works independently to execute small to medium projects, but you’ll also have the opportunity to collaborate with cross functional teams to continually improve your level of knowledge about JPMorgan Chase’s business and relevant technologies.
Job responsibilities
As a Site Reliability Engineer II at JPMorgan Chase within Asset and Wealth Management, you will use technology to solve business problems and leverage software engineering best practices as we strive towards excellence. This role often works independently to execute small to medium projects, but you’ll also have the opportunity to collaborate with cross functional teams to continually improve your level of knowledge about JPMorgan Chase’s business and relevant technologies.
Job responsibilities
- Designs, develops, and delivers software solutions, applying structured problem decomposition and technical troubleshooting to address complex engineering challenges
- Writes secure, high-quality production code and maintains reliable algorithms/services that meet system and operational requirements
- Produces and maintains architecture and design artifacts for complex applications, ensuring implementations adhere to defined design constraints
- Implements and continuously improves reliability and release practices through automated CI/CD pipelines and engineering best practices
- Collaborate with software engineers, stakeholders, and production support partners to resolve complex problems and proactively address issues before they impact customers
- Analyzes large, diverse datasets to generate insights, visualizations, and reporting that drive continuous improvement of applications and systems
- Uses enterprise-authorized AI capabilities to accelerate troubleshooting and operational analysis, validating outputs and handling operational data in line with sensitivity and security requirements
- Contributes to engineering communities of practice and participates in events exploring new and emerging technologies
- Fosters an inclusive team culture grounded in diversity, opportunity, inclusion, and mutual respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
SRE mindset and working knowledge of reliability principles, including availability, scalability, incident management, and iterative improvement - Expert level in the programming on Python. Experience designing and building APIs using popular frameworks such as Flask, Fast API
- Hands-on experience with system design, application development, testing, and operational stability in a large-scale distributed environment
- Experience maintaining a Cloud-base infrastructure
- Familiar with observability such as white and black box monitoring, service level objective alerting, and telemetry collection/visualization using tools such as Grafana, Dynatrace, Prometheus, Phoenix, Splunk, OpenTelemtry and others
- Emerging knowledge of software, applications and technical processes within a given technical discipline (e.g., Cloud, artificial intelligence, Android, etc.)
- Emerging knowledge of continuous integration and continuous delivery tools (e.g., Jenkins, Jules, Spinnaker, BitBucket, GitLab, Terraform, etc.)
- Demonstrated ability to work effectively with enterprise-authorized AI-assisted engineering tools within the work environment as a core part of modern software and reliability engineering, including the ability to validate outputs for correctness, performance, and security, and to handle inputs/outputs in accordance with data sensitivity requirements
- Production support / on-call experience, including incident triage, mitigation, root cause analysis, and driving post-incident improvements
Preferred qualifications, capabilities, and skills
- Experience in a financial institution, preferably supporting Front Office platforms and time-sensitive, high-availability workloads
- Knowledge on Terraform, containers and container orchestration, especially Kubernetes preferred
- Knowledge of FinOps principles, cloud financial management, and cost optimization techniques
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