Job responsibilities

• Demonstrates expertise in site reliability principles and demonstrates an understanding of the fine balance between features efficiency and stability
• Effectively negotiates with peers and executive partners to ensure optimal outcomes for all 
• Drives the adoption of site reliability practices throughout the organization

• Drives reuse-first adoption of enterprise-authorized AI capabilities within the work environment to improve reliability operations and customer experience outcomes with human-in-the-loop validation and appropriate handling of sensitive data

• Ensures your teams demonstrate site reliability best practices with the ability to demonstrate this empirically through stability and reliability metrics
• Drives a culture of continual improvement and solicits real-time feedback to improve the customer’s experience
• Ensures your team collaborates with other teams within your group’s specialization and avoids duplication of work where possible
• Follows blameless data-driven post-mortem strategies and conducts regular team debriefs to enable learning from both successes and mistakes
• Provides personalized coaching for entry to mid-level team members 
• Ensures your team documents and shares their knowledge and innovations via internal forums communities of practice guilds and conferences 
• Establishes team standards for AI-assisted reliability workflows across automation and delivery practices ensuring traceability/auditability resiliency and security controls.

Required qualifications capabilities and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Advanced proficiency in site reliability culture and principles and can demonstrate how to implement site reliability across application and platform teams while avoiding common pitfalls

• Experience leading teams in the safe use of enterprise-authorized AI capabilities within the work environment for reliability engineering workflows including validation habits and awareness of data sensitivity.

• Ability to set and reinforce organization-level practices for reviewing AI-assisted recommendations and escalating uncertain decisions while maintaining resiliency security and auditability outcomes.

• Experience leading technologists to manage and solve complex technological issues at a firmwide level
• Ability to influence the team’s culture by championing innovation and change for success
• Experience hiring developing and recognizing talent
• Proficiency in at least one programming language (e.g. Python Java Spring Boot .Net etc.)
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g. cloud artificial intelligence machine learning mobile etc.)
• Proficiency in continuous integration and continuous delivery tools (e.g. Jenkins GitLab Terraform etc.)
• Experience with container and container orchestration (e.g. ECS Kubernetes Docker etc.)and  troubleshooting common networking technologies and issues

Preferred qualifications capabilities and skills

• Ability to code and demonstrate data fluency

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.