Cloud-Native Engineer

Artech
Phoenix, AZ, United States
16 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$83,200 - $93,600
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Application Performance Management Cloud Computing Cloud Engineering Code Review Continuous Integration DevOps Github Python (Programming Language) Software Engineering Google Cloud
+12 more
System Availability Large Language Models Technical Debt Infrastructure as Code (IaC) Agentic-AI Containerization Kubernetes Deployment Automation Cloud Optimization Terraform Docker Jenkins

Job description

β€œDesign, develop and maintain cloud-native solutions on AWS/GCP using modern software engineering practices. Β· Design containerised applications using Kubernetes, EKS, Docker and related cloud-native technologies. Β· Implement Infrastructure as Code (IaC) and automate provisioning, deployment and operational workflows. Β· Build and maintain CI/CD pipelines leveraging GitHub Actions, Jenkins and related DevOps toolchains. Β· Collaborate with architects, product owners and application teams to modernise workloads and adopt cloud best practices. Β· Troubleshoot issues, optimise application performance and improve platform reliability. Β· Identify technical debt, drive continuous improvement initiatives and evaluate emerging technologies in Cloud and AI. Β· Contribute to engineering standards, code reviews, documentation and knowledge-sharing activities. Β· Work effectively both independently and collaboratively within a global team environment.”, Design| develop and maintain cloud-native solutions on AWS/GCP using modern software engineering practices. Design containerised applications using Kubernetes| EKS| Docker and related cloud-native technologies. Implement Infrastructure as Code (IaC) and automate provisioning| deployment and operational workflows. Build and maintain CI/CD pipelines leveraging GitHub Actions| Jenkins and related DevOps toolchains. Collaborate with architects| product owners and application teams to modernise workloads and adopt cloud best practices. Troubleshoot issues| optimise application performance and improve platform reliability. Identify technical debt| drive continuous improvement initiatives and evaluatee merging technologies in Cloud and A

Requirements

Software Engineering, Cloud Computing, Cloud Computing, Software Engineering, GCP (Good Clinical Practices), Amazon Web Services (AWS), Docker, Software Design, GitHub, DevOps, β€œExperience in Python development, AWS/GCP, Kubernetes, containerization, DevOps automation (Terraform/IaC), and CI/CD pipelines, with additional exposure to Agentic AI and LLM integration frameworks.”

Keyword: β€œPython development, AWS/GCP, Kubernetes, containerization, DevOps automation (Terraform/IaC), and CI/CD pipelines, Agentic AI and LLM integration framework”

Experience Required : 5-6 Years

Role Descriptions: Experience in Python development AWS/GCP Kubernetes containerization DevOps automation(Terraform/IaC) and CI/CD pipelines with additional exposure to Agentic AI and LLM integration frameworks. Roles & Responsibilities Design develop and maintain cloud-native solutions on AWS/GCP using modern software engineering practices. Design containerised applications using Kubernetes EKS Docker and related cloud-native technologies. Implement Infrastructure as Code (IaC) and automate provisioning deployment and operational workflows. Build and maintain CI/CD pipelines leveraging GitHub Actions Jenkins and related DevOps toolchains. Collaborate with architects product owners and application teams to modernise workloads and adopt cloud best practices. Troubleshoot issues optimise application performance and improve platform reliability. Identify technical debt drive continuous improvement initiatives and evaluatee merging technologies in Cloud and A
Essential Skills: Experience in Python development AWS/GCP Kubernetes containerization DevOps automation(Terraform/IaC) and CI/CD pipelines with additional exposure to Agentic AI and LLM integration frameworks.                

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