Lead Software Engineer- AWS Terraform -Infrastructure as Code (IaC)
Summary
The Lead Software Engineer will design and manage scalable cloud infrastructure on AWS using Terraform and CI/CD automation. The role involves driving the adoption of AI-assisted engineering practices while ensuring system reliability, security, and observability.
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 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)