Join a high-performing team where your expertise shapes the future of infrastructure at a global leader. Grow your skills and make a lasting impact.
As a Lead Infrastructure Engineer at JPMorganChase within the Chief Technology Office team, you apply deep knowledge of software, applications, and technical processes to infrastructure engineering. You will continue to evolve your technical and cross-functional expertise, collaborating across domains to deliver excellence. We value your contributions and encourage you to expand your skills in a supportive, innovative environment.
Job responsibilities
- Apply technical expertise and problem-solving methodologies to projects of moderate scope
- Drive workstreams or projects involving infrastructure engineering technologies
- Collaborate with other platforms to architect and implement changes for issue resolution and modernization
- Execute creative solutions for design, development, and technical troubleshooting
- Consider upstream/downstream data and systems implications and advise on mitigation actions
- Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.
- Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations**. **
Required qualifications, capabilities and skills
- Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
- 8+ years of experience in SRE, DevOps, or platform automation roles
- Strong proficiency in scripting and programming languages such as Python, Bash, PowerShell, or Go
- Hands-on experience with CI/CD tools (Jenkins, Spinnaker, GitLab CI, or equivalent)
- Experience with Infrastructure as Code (Terraform, Ansible, CloudFormation)
- Strong experience with monitoring and observability tools (Dynatrace, Splunk, Grafana, Datadog)
- Experience with cloud platforms (AWS, Azure, or GCP)
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.
- Hands-on experience in supporting infrastructure platform and SRE for BI tools such as SAP BusinessObjects, ThoughtSpot, Tableau, Qlik Sense, or IBM Cognos
- Hands-on experience with ServiceNow, JIRA ticketing tools
Preferred qualifications, capabilities and skills
- Familiarity with secrets management, least-privilege access, and security best practices
- Experience with Snowflake, Databricks, or other cloud data platforms
- Knowledge of SDLC processes, Agile/Scrum methodologies, and change management
- Experience with Autosys, Control-M, or similar job scheduling tools