JPMorganChase
Lead Infrastructure Engineer - DevOps (AWS, EKS, Terraform, Python)
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Lead infrastructure engineering for a quantitative technology stack: provision and manage AWS resources, implement CI/CD, automate infrastructure with Terraform and Python, operate Kubernetes/EKS and Docker, monitor environments, support developers and ETL processes, mentor junior engineers, address security/compliance, and apply enterprise-authorized AI practices to improve resiliency and automation.
Assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. Your role will be instrumental in shaping the future at one of the world's largest and most influential companies.
As a Lead Infrastructure Engineer at JPMorganChase within the Asset and Wealth Management, you apply deep knowledge of software, applications, and technical processes within the infrastructure engineering discipline. Continue to evolve your technical and cross-functional knowledge outside of your aligned domain of expertise.
Job responsibilities
- Build, manage, and monitor the quantitative technology stack.
- Provision AWS resources to support expanding platform needs. Implement CI/CD tools and source control using Git and BitBucket
- Manage upgrade cycles and address resource security findings
- Mentor and guide junior engineers, promoting best practices in security, compliance, and cloud-native development.
- Develop automation tools and/or code to manage and monitor the infrastructure.
- Provide technical support during software development. Troubleshoot any issues that arise in the test and computational environments
- Maintain inventory of the relevant environments.
- Assist development team in debugging environment specific issues. Take part in operational support of ETL processes
- Stay current with industry trends and source new ways for our business to improve
- 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
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Bachelor’s Degree in Computer Science, Engineering, Software Engineering, or a relevant field
- Expertise in administration of AWS Services like EC2, EKS, S3, Lambda, RDS/Aurora, ElastiCache, ELB, EMR, CodeDeploy, and CloudWatch
- Strong Experience working with Terraform. Strong Experience working with Kubernetes and Docker.
- Experience using Git. Experience with FinOps best practices for cloud architectures. Experience with project workflow tools such as Jira in an Agile-Scrum environment. Experience with Linux-based infrastructures, and Linux administration
- Strong communication & interpersonal skills and ability to explain protocol and processes to the team. Strong troubleshooting skills with the ability to spot issues before they become problems
- Experience working with relational databases such as PostgreSQL. Experience with administration of job orchestration tools such as Airflow
- Ability to deploy software written in Python
- 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.
Preferred qualifications, capabilities, and skills
- Experience working with relational databases such as PostgreSQL
- Experience with administration of job orchestration tools such as Airflow
- Ability to deploy software written in Python
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