Lead Software Engineer - Public Cloud & AI

Job Description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Public Cloud Platform Engineer at JPMorgan Chase within the Global Technology team, you will be guiding application teams on moving to public cloud, support with maintaining, and support resolving production incidents that impact our customers, clients, and businesses around the globe.

Job responsibilities

Drive, support, and deliver on a strategy to operate on a build broad use of Amazon's utility computing web services (e.g., AWS EC2, AWS S3, AWS RDS, AWS CloudFront, AWS EFS, CloudWatch, EKS)

Identify opportunities to improve resiliency, availability, secure, high performing platforms in Public Cloud using JPMC best practices

Improve reliability, quality, and reduce time to resolve issues in production incidents on software applications

Measure and optimize system performance, with an eye toward pushing our capabilities forward, getting ahead of customer needs, and innovating to continually improve

Provide primary operational support and engineering for the public cloud platform

Debug and optimize systems and automate routine tasks.

Collaborate with a cross-functional team to identify potential risks in production and opportunities to improve user experiences at every interaction.

Drive work streams to ensure Applications meet strict non-functional requirements for Public Cloud On-boarding

Evaluate production readiness through game days, resiliency tests and chaos engineering exercises.

Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services

Monitor metrics and program health, anticipate and clear blockers, manage escalations

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience

A deep understanding of business technology drivers and their impact on architecture design, performance and monitoring, best practices

Experience/knowledge building or supporting web environments on AWS, which includes working with services like EC2, ELB, RDS, and S3

Experience using DevOps tools in a cloud environment, such as Ansible, Artifactory, Docker, GitHub, Jenkins, Kubernetes, Maven etc.

Experienceacross the SDLC process – Design and/or Development and/or support

Experience/Knowledge using monitoring solutions like CloudWatch, Prometheus, Datadog

Experience/Knowledge of writing Infrastructure-as-Code (IaC), using tools like CloudFormation or Terraform

Experience with one or more public cloud platforms like AWS, GCP, Azure

Experience with automation of Infrastructure tasks using Python or other languages

Knowledge in leveraging AI/LLM tools to enable self-service on diagnosing infrastructure errors/failures

Preferred qualifications, capabilities, and skills

A proactive approach to spotting problems, areas for improvement, and performance bottlenecks

SRE mindset Culture/Approaches: To run better production systems by creating engineering solutions to operational problems.

#J-18808-Ljbffr