Lead Software Engineer- AWS Terraform -Infrastructure as Code (IaC)

JPMorgan Chase & Co.

Plano (TX)

On-site

USD 150,000 - 210,000

Full time

3 days ago
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Job summary

JPMorgan Chase & Co. in Plano, TX seeks a Lead Software Engineer to design and deliver secure, scalable technology products across business functions. You will guide an agile team to build trusted cloud infrastructure and advance automation.

The role emphasizes IaC, AI-assisted tooling, observability, and on-call incident response. You will collaborate with developers to improve system design, performance, and security, while upholding enterprise standards and best practices.

Qualifications

  • 5+ years of practical software engineering experience.
  • Hands-on AWS experience with ECS, EKS, Lambda, API Gateway, S3, DynamoDB, IAM, VPC, CloudWatch, KMS.
  • Experience using AI-assisted development tools with secure outputs.
  • Strong knowledge of secure coding, testing, and resiliency practices.
  • Proficiency in Terraform and IaC best practices.
  • Networking fundamentals and container orchestration (Docker, Kubernetes).
  • Experience with CI/CD tools: Jenkins, Spinnaker, Nexus, ECR, JFrog, GitOps.
  • Fluency in scripting languages: Python, Bash, Go.

Responsibilities

  • Design, build, and operate scalable cloud infrastructure with reliability, security, and operability.
  • Develop and maintain Infrastructure as Code (IaC) patterns (reusable modules, consistent standards, safe deployments).
  • Improve CI/CD and deployment automation across services and environments.
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Own and improve observability: monitoring, alerting, logging, dashboards, and actionable runbooks.
  • Participate in on-call rotations and incident response; drive high-quality postmortems and follow-through.
  • Partner closely with developers to improve system design, performance, and operational maturity.
  • Strengthen engineering quality via PR reviews, shared standards, and knowledge sharing.

Skills

AWS
Terraform
CI/CD
Observability
AI-assisted development
Security practices
Python
Go
Bash
Docker
Kubernetes
Networking fundamentals
Incident response
Code reviews
On-call rotations
Scripting

Education

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

Tools

ECS
EKS
Lambda
API Gateway
S3
DynamoDB
IAM
VPC
CloudWatch
KMS
Jenkins
Spinnaker
Nexus
ECR
JFrog
GitOps
Docker
Kubernetes

Job description

As a Lead Software Engineer at JPMorganChase Commercial and Investment Banking, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job Responsibilities
  • Design, build, and operate scalable cloud infrastructure with a strong focus on reliability, security, and operability
  • Develop and maintain Infrastructure as Code (IaC) patterns (reusable modules, consistent standards, safe deployments)
  • Improve CI/CD and deployment automation across services and environments
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Own and improve observability: monitoring, alerting, logging, dashboards, and actionable runbooks
  • Participate in on-call rotations and incident response; drive high-quality postmortems and follow-through
  • Partner closely with developers to improve system design, performance, and operational maturity
  • Strengthen engineering quality via PR reviews, shared standards, and knowledge sharing
Required qualifications, capabilities, and skills
  • A. Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on practical experience on AWS: ECS, EKS, Lambda, API Gateway, S3, DynamoDB, IAM, VPC, CloudWatch, KMS
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Proficient in Terraform (modules, state management, workspaces)
  • Advanced understanding of Infrastructure as Code best practices (strong IaC and CI/CD patterns)
  • Good hands on Networking fundamentals: load balancers, DNS, firewalls, VPNs , Jenkins (pipelines, Groovy, shared libraries), Spinnaker (pipelines, deployment strategies, canary/blue-green), GitOps workflows, Containers and orchestration: Docker, Kubernetes/EKS
  • Artifact management: Nexus, ECR, JFrog
  • Experience with R reliability, Observability, Security, Compliance, Scripting and automation using Python, Bash, Go , JSON and Restful API
Preferred qualifications, capabilities, and skills
  • Good to have performance engineering basics
  • nice to have Cost optimization experience (FinOps mindset)
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