AWS cloud engineer

Machine Learning Technologies, LLC; City of Albany (NY); On-site; USD 110,000 - 150,000; Full time

Job summary

Machine Learning Technologies, LLC seeks an experienced AWS Cloud Engineer to design, implement, and optimize scalable cloud infrastructure. You will drive automation and secure operations across DevOps environments, using IaC and modern CI/CD pipelines.

The role requires hands-on experience with Terraform, CloudFormation, Jenkins, GitHub Actions, GitLab CI, and CodePipeline, plus Docker, Kubernetes, and Helm.

Qualifications

• Experience designing, deploying, and managing scalable AWS cloud infrastructure.
• Proven ability to implement IaC with Terraform and CloudFormation.
• Hands-on experience with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, AWS CodePipeline).
• Container orchestration with Docker, Kubernetes, and Helm; scripting in Python and Bash.

Responsibilities

• Design, deploy, and manage scalable AWS cloud infrastructure using IaC tools like Terraform and CloudFormation.
• Develop, maintain, and optimize CI/CD pipelines with Jenkins, GitHub Actions, GitLab CI, and CodePipeline.
• Implement release automation and deployment strategies to improve software delivery.
• Manage containerized apps with Docker, Kubernetes, and Helm for deployment and scaling.
• Develop automation scripts in Python and Bash for cloud operations and infra management.
• Implement IAM, encryption, and security controls per AWS security best practices.
• Monitor infrastructure with CloudWatch, Prometheus, and Grafana; identify and respond to threats.
• Collaborate with development, security, and operations teams to improve reliability and automation.

Skills

AWS cloud

DevOps

IaC

CI/CD

Python scripting

Security best practices

Monitoring

Tools

Terraform

CloudFormation

Jenkins

GitHub Actions

GitLab CI

AWS CodePipeline

Docker

Kubernetes

Helm

Prometheus

Grafana

CloudWatch

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

We are looking for an experienced AWS Cloud Engineer with strong expertise in AWS cloud infrastructure, DevOps automation, Infrastructure as Code (IaC), CI/CD pipelines, containerization, and cloud security. The ideal candidate will be responsible for designing, implementing, managing, and optimizing scalable and secure cloud infrastructure while driving automation and continuous delivery across DevOps environments.

Key Responsibilities

• Design, deploy, and manage scalable AWS cloud infrastructure using Infrastructure as Code (IaC) tools such as Terraform and AWS CloudFormation.
• Develop, maintain, and optimize CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, and AWS CodePipeline.
• Implement end-to-end release automation, deployment strategies, and DevOps best practices to improve software delivery.
• Manage containerized applications using Docker, Kubernetes, and Helm for deployment, orchestration, and scaling.
• Develop automation scripts using Python and Bash to streamline cloud operations and infrastructure management.
• Implement AWS security best practices, including IAM, access management, encryption, and security controls.
• Monitor cloud infrastructure, identify security vulnerabilities, respond to potential threats, and ensure compliance with organizational security standards.
• Implement monitoring and observability solutions using Amazon CloudWatch, Prometheus, and Grafana.
• Troubleshoot infrastructure, deployment, performance, and operational issues across AWS environments.
• Collaborate with development, security, and operations teams to improve cloud reliability, scalability, and automation.

Required Technical Skills

• Strong hands-on experience with AWS Cloud Services and cloud infrastructure management.
• Proficiency in Terraform and CloudFormation.
• Experience with CI/CD tools: Jenkins, GitHub Actions, GitLab CI, and AWS CodePipeline.
• Hands‑on experience with Docker, Kubernetes, and Helm.
• Strong scripting skills in Python and Bash.
• Knowledge of AWS security services, IAM, cloud security controls, and compliance frameworks.
• Experience with monitoring tools such as Amazon CloudWatch, Prometheus, and Grafana.
• Strong understanding of DevOps practices, automation, continuous integration, and continuous deployment.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.