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 Community and Consumer Banking, you will play a pivotal role in leveraging GenAI and agentic AI to drive technology infrastructure cost optimization across both on-premises and cloud environments.This hands-on position centers on developing, implementing, and evangelizing GenAI-driven solutions and intelligent agents that continuously optimize spend, automate cost management, and deliver maximum value from our application infrastructure investments. You will collaborate with cross-functional teams to architect, build, and deploy AI-powered agents that enhance reliability, scalability, security, and cost effectiveness of our banking platforms.

Job Responsibilities

Lead the development and integration of GenAI-powered agents into all phases of the application and infrastructure lifecycle to automate cost optimization and efficiency improvements
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.
Discover, analyze, and prioritize cloud cost optimization opportunities using GenAI models and intelligent agents calculate potential savings and benefits leveraging data repositories, reporting, and ETL tools
Collaborate with teams to design, implement, and scale GenAI agent-based cost optimization recommendations and best practices.
Architect and develop automation runbooks and Policy as Code initiatives to drive cloud cost efficiencies powered by GenAI agents and strengthen Cost Governance.
Guide end users and development teams in adopting cost-effective architectural, operational, and performance decisions.
Communicate FinOps principles and GenAI agent capabilities to key stakeholders and leadership, identifying waste and maintaining dashboards that showcase cost savings
Serve as the primary contact and owner for FinOps-specific GenAI applications and agent processes, ensuring compliance and up-to-date documentation (Confluence experience an advantage).
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

5+ years of experience in infrastructure engineering, software deployment, or related fields.
Strong understanding of cloud infrastructure and multiple cloud technologies with experience using infra-as-code technologies (e.g., Terraform).
Infrastructure engineering technical depth such as hardware, networking, databases, storage, deployment, integration, automation, scaling, resilience, and performance assessments.
Proven experience leveraging GenAI and agentic AI to automate and develop enterprise software delivery and cost optimization solutions
Hands-on experience implementing FinOps and GenAI agents to optimize AWS cloud costs, with deep understanding of levers available to optimize cloud costs.
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.
Strong communication and collaboration skills and a demonstrated ability to develop technical and cross-functional knowledge outside of the product domain.
Proficient in coding with modern scripting languages and infrastructure as code practices.
Advanced understanding of AWS services for Traditional Compute, Containerization, and Serverless architectures.
Expert-level experience in developmental toolsets including Jira, BitBucket, and Confluence.

Preferred Qualifications, Capabilities, and Skills

Degree in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines.
Certifications such as FinOps Practitioner or FinOps Professional.
AWS certifications such as Certified Cloud Practitioner.
Experience leading automation projects using GenAI and agentic AI.

Lead Infrastructure Engineer - GenAI & CloudFormation