JP Morgan Chase

Runs a consumer bank and an investment bank

Lead Infrastructure Engineer - Multiple Teams

Cloud EngineeringPosted on Nov 9

Full-timeNo salary listedIn-person

About the Job

Requirements

Formal training or certification in infrastructure engineering concepts and at least 5 years of 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 across hardware, networking, databases, storage, deployment, integration, automation, scaling, resilience, and performance assessments.
Proven experience leveraging generative AI and agentic AI to automate and develop enterprise software delivery and cost optimization solutions.
Hands-on experience implementing FinOps and generative AI agents to optimize AWS cloud costs, with deep understanding of available optimization levers.
Strong understanding of the FinOps Foundation Framework, its capabilities, lifecycle, and domains; proficiency in 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 in the work environment for infrastructure engineering workflows, with validation habits and awareness of data sensitivity.
Ability to review and validate AI-assisted recommendations before implementation, escalate when uncertain, and ensure outcomes align with resiliency, security, and auditability expectations.

Responsibilities

Lead development and integration of generative AI-powered agents across the application and infrastructure lifecycle to automate cost optimization and efficiency improvements.
Discover, analyze, and prioritize cloud cost optimization opportunities using generative AI models and intelligent agents; calculate potential savings and benefits using data repositories, reporting, and ETL tools.
Collaborate with teams to design, implement, and scale agent-based cost optimization recommendations and best practices.
Architect and develop automation runbooks and Policy as Code initiatives powered by generative AI agents to drive cloud cost efficiencies and strengthen cost governance.
Guide end users and development teams in adopting cost-effective architectural, operational, and performance decisions.
Communicate FinOps principles and generative AI agent capabilities to stakeholders and leadership, identify waste, and maintain dashboards showcasing cost savings.
Serve as the primary contact and owner for FinOps-specific generative AI applications and agent processes, ensuring compliance and current documentation.
Use enterprise-authorized AI capabilities in the work environment to accelerate infrastructure analysis and design documentation, validate outputs, and handle operational data according to sensitivity and security requirements.
Drive a workstream or project involving one or more infrastructure engineering technologies, and work with other platforms to architect and implement changes that resolve issues and modernize organizational and technology processes.
Consider upstream and downstream data, systems, and technical implications, and advise on mitigation actions.
Apply reuse-first, AI-assisted practices in delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable, auditable, and aligned with resiliency and security expectations.

Desired Qualifications

AWS engineering or architect certifications.
FinOps Practitioner or FinOps Professional certification.
Experience leading automation projects using generative AI and agentic AI.
Advanced certifications in infrastructure engineering, cloud technologies, or 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 - 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.

About the Company

JP Morgan Chase

Runs a consumer bank and an investment bank

JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1799

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