Principal AWS DevOps Engineer

Job Title : Principal AWS DevOps Engineer

Experience: 5+ Years

Location: Remote

Employment Type: Contract

Duration : 3 Months (Short Term) We are seeking an experienced AWS DevOps Engineer to build, automate, and manage the cloud infrastructure powering an AI-driven enterprise platform. The platform consists of Python-based backend services, AI/ML workloads, LLM integrations, ReactJS frontend applications, and cloud-native microservices deployed on AWS. The ideal candidate will possess deep expertise in Infrastructure as Code (Terraform), CI/CD automation, container orchestration, cloud security, and scalable deployment architectures for AI/ML applications.

Responsibilities: Cloud Infrastructure & Platform Engineering

• Design, implement, and manage highly available AWS infrastructure supporting AI/ML workloads.
• Architect cloud-native environments optimized for scalability, performance, reliability, and cost efficiency.
• Manage AWS networking, security, storage, and compute service
• Support multi-environment deployments (Development, QA, UAT, Production

Infrastructure as Code (Iac)

• Develop and maintain infrastructure using Terraform
• Create reusable Terraform modules for cloud resources and platform service
• Automate provisioning and configuration management across environment
• Maintain version-controlled infrastructure repositories and deployment standards

CI/CD Automation

• Design and maintain CI/CD pipelines for:
• Python backend services
• ReactJS frontend applications
• AI/ML model deployment pipelines
• Infrastructure deployments using Terraform
• Automate code quality checks, testing, security scans, container builds, and releases.
• .Implement GitOps and DevSecOps practices.

AI/ML Platform Operations

• Deploy and manage AI/ML services on AWS
• Support model training, inference, and deployment workflows.
• Manage GPU-enabled infrastructure where requires
• Automate model packaging and deployment processes.
• Integrate AI/ML services with enterprise applications

Containerization & Orchestration

• Build and manage containerized applications using Docker.
• Deploy and manage workloads on Amazon EKS (Kubernetes)
• Configure auto-scaling, rolling deployments, blue-green deployments, and canary releases.
• Optimize container performance and resource utilization

Monitoring, Logging & Reliability

• Implement platform observability using monitoring and logging tools
• Create dashboards and alerts for infrastructure, applications, APIs, and AI workloads
• Conduct root cause analysis and incident resolution
• Define and maintain SLOs, SLAs, and operational metrics.

Security & Compliance

• Implement IAM policies, secrets management, encryption, and security controls.
• Integrate vulnerability scanning and compliance checks into CI/CD pipelines.
• Enforce security best practices across infrastructure, containers, and applications.
• Support enterprise-grade governance and compliance requirements.

Required Technical Skills. Cloud Platform Strong hands-on experience with AWS services including:

• EC2
• ECS
• EKS Lambda
• S3CloudFront
• VPC
• IAMCloud
• API Gateway Secrets
• Manager AWS Systems Manager

Infrastructure as Code

• Terraform (Mandatory)
• Terraform Cloud/Enterprise (Preferred)
• Remote State Management
• Module Development
• Environment Automation

CI/CD & DevOps

• GitHub Actions
• Jenkins
• GitLab CI/CD
• AWS CodePipeline
• AWS CodeBuild
• GitOps methodologies

Container & Orchestration

• Docker
• Kubernetes
• Amazon EKS
• Helm Charts

Backend Technologies Experience supporting deployment and operations of:

• Python
• FastAPI
• Flask
• Django
• REST APIs
• Microservices Architecture

Frontend Technologies Experience supporting deployment and release management of:

• ReactJS

AI/ML & Data Platforms Experience with one or more of:

• OpenAI integrations
• Vector Databases
• ML Model Deployment Pipelines
• MLflow
• LangChain
• RAG-based Architectures

Monitoring & Observability

• CloudWatch
• Prometheus
• Grafana
• ELK/OpenSearch

Scripting & Automation

• Python
• Bash/Shell Scripting
• YAML
• JSON

Preferred Experience

• Experience managing AI-powered SaaS or enterprise platforms.
• Experience deploying LLM-based applications and AI agents.
• Experience supporting RAG architectures and vector databases.
• Experience implementing MLOps best practices.
• Experience working in Agile/Scrum product teams.