Lead Infrastructure Engineer – GenAI/AI Automation/AWS

Lead GenAI and agentic AI initiatives to optimize technology infrastructure costs across on-prem and cloud environments at scale now.

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 - GenAI/AI Automation/AWS at JPMorganChase within the Consumer and Community Banking team, 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 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 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 to 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). 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. Drives a workstream or project consisting of one or more infrastructure engineering technologies and works with other platforms to architect and implement changes required to resolve issues and modernize the organization and technology processes Strongly considers upstream and downstream data and systems or technical implications and advises on mitigation actions 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 infrastructure engineering concepts and 5+ years applied experience Strong understanding of cloud infrastructure and multiple cloud technologies with experience using public cloud cost management and optimization tools. 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. Excellent problem-solving skills and ability to execute creative, GenAI-driven solutions for technical challenges. Strong communication and collaboration skills and a demonstrated ability to develop technical and cross-functional knowledge outside of the product domain. Strong understanding of the FinOps Foundation Framework, capabilities, lifecycle, and domains; Proficient in coding with modern scripting languages and infrastructure as code practices. Advanced understanding of AWS services for Traditional Compute, Containerization, and Serverless architectures. 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 AWS Engineering or Architect certifications Certifications such as FinOps Practitioner or FinOps Professional. Experience leading automation projects using GenAI and agentic AI. Advanced certifications in infrastructure engineering, cloud technologies, or automation. Exceptional verbal and written communication skills.