Infrastructure Developer (DevOps) in Mumbai, India is listed on Jobeax. Browse 30,000+ vacancies available.
You belong to the top echelon of talent in your field. At one of the world's most iconic financial institutions, where infrastructure is of paramount importance, you can play a pivotal role.
As an Infrastructure Engineer III at JPMorganChase within the Commercial & Investment Bank Payments Technology team, you utilize strong knowledge of software, applications, and technical processes within the infrastructure engineering discipline. Applies technical knowledge and problem-solving methodologies to projects of moderate scope, with a focus on improving data and systems running at scale, and ensures end to end monitoring of applications
Uses enterprise-authorized AI capabilities within the work environment to accelerate monitoring and capacity analysis and documentation, validating outputs and handling operational data according to sensitivity and security requirements.
Executes conventional approaches to build or break down technical problems while considering upstream and downstream data and systems or technical implications
Drives the daily activities supporting the standard capacity process applications and partners with application and infrastructure teams to identify potential capacity risks and govern remediation statuses
Accountable for making significant decisions for a project consisting of multiple technologies and applications
Applies reuse-first, AI-assisted approaches to identify recurring capacity risks and improve remediation workflows, ensuring changes are validated and aligned to resiliency and security expectations.
Formal training or certification on infrastructure engineering concepts and 3+ years applied experience
Hands-onexperience in DevOps, with a strong focus on Jenkins, Kubernetes, and SDLC pipelines.
Proven experience in deployment architecture and cloud best practices.
Experience with managing EOL components and driving process improvements.
Experience with Helm for Kubernetes package management.
Experience with monitoring and observability tools like Grafana, Dynatrace, Splunk, DataDog, etc
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.
Experience in financial services or a related industry.
Certifications in cloud platforms (e.g., AWS, Azure, Google Cloud).