Lead Infrastructure Engineer - GenAI & CloudFormation

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.