GenAI/AWS Infra Engineer — AI-Driven Cloud Optimizer

JPMorgan Chase & Co.

Wilmington (NC)

On-site

USD 61,000 - 101,000

Full time

5 days ago

Be an early applicant

Get a reply from this employer

Your resume and cover letter, tailored to exactly what they’re hiring for.

Get past ATS filters

Job summary

JPMorgan Chase & Co. is seeking an Infrastructure Engineer III with GenAI/AI Automation and AWS expertise in Wilmington, NC.

You will apply advanced technical knowledge to design, implement, and optimize cloud-based infrastructure across multiple platforms, focusing on cost-efficiency and reliability. You will collaborate with cross-functional teams to deploy scalable GenAI-driven solutions, validate outcomes, and ensure security, resiliency, and auditability while following FinOps best

Qualifications

Formal training or certification in infrastructure engineering concepts; 3+ years of applied experience.
Strong understanding of cloud infrastructure and cost management tools.
Technical depth in infrastructure engineering: hardware, networking, databases, storage, deployment, automation, scaling, resilience, and performance assessment.
Experience using GenAI/agentic AI to automate and develop enterprise software delivery and cost-optimization solutions.
Hands-on FinOps and GenAI in AWS cloud optimization; AI automation.
Experience with enterprise AI capabilities in infrastructure workflows; data sensitivity awareness.
Ability to review AI-assisted recommendations for resiliency, security, and auditability.
Strong problem-solving; creative GenAI-driven solutions; familiarity with FinOps Foundation Framework.
Advanced understanding of AWS services for compute, containerization, serverless.
Scripting language proficiency.
Cross-cloud experience and cloud migrations.

Responsibilities

Apply technical knowledge to moderate-scope projects improving data and systems at scale, with end-to-end monitoring.
Identify and prioritize cloud cost-optimization opportunities using GenAI and intelligent agents; estimate savings from data and ETL tools.
Design, implement, and scale GenAI agent-based cost-optimization recommendations and practices.
Use enterprise AI tools to support monitoring, capacity analysis, and documentation; validate results with security and sensitivity requirements.
Resolve technical nuances and determine appropriate escalation.
Decompose technical problems considering upstream and downstream systems and data.
Lead daily activities for capacity-process applications and oversee remediation of capacity risks.
Make significant decisions for multi-technology projects.
Use reuse-first AI-assisted methods to improve remediation workflows and validate resiliency and security.