Cloud Platform Engineer – AWS, Python, DevOps & AI/LLM

Résumé du poste

Build and share reusable platform patterns, pipelines, and AI agents while ensuring operational simplicity. Design secure, scalable cloud systems and provide coaching through working code and automation.

Détails du poste

Cloud Platform Engineer – AWS, Python, DevOps & AI/LLM Required Skillsets: • 3–5+ years of hands-on CI/CD, cloud, and platform engineering experience in enterprise environments. • Strong proficiency in Python for automation, API integrations, infrastructure tooling, agent services, and production scripting. • Working experience with at least one additional language or ecosystem such as Java, .NET, Groovy, or Node.js. • Hands-on AWS experience designing or operating production workloads. • Practical knowledge of AWS IAM, including roles, policies, trust relationships, cross-account access, least privilege, and service-to-service authentication. • Production experience building and deploying containers with Docker and a container platform such as Kubernetes, Amazon ECS, or Amazon EKS. • Experience building or integrating AI/LLM-based tools or agents in production or near-production environments. • Strong understanding of LLMOps concepts: prompt management, tool use, agent architectures, evaluation, observability, and reliability. • Experience with Git-based workflows, build automation, and release pipelines at scale. • Hands-on experience with Infrastructure as Code, configuration management, and cloud-native deployments. • DevSecOps mindset — security is a design constraint, not a checklist item. Good to Have Skills: • Experience with AWS services such as EKS, ECS, ECR, Lambda, Bedrock, CloudWatch, S3, Secrets Manager, Systems Manager, and VPC. • Experience with Terraform, CloudFormation, or AWS CDK. • Experience designing multi-account AWS environments and implementing enterprise identity and access patterns. • Familiarity with Kubernetes operations, Helm, service accounts, ingress, networking, and workload security. • Experience integrating AI into developer platforms or enterprise tooling, rather than only building standalone applications. • Prior work on agentic orchestration frameworks such as LangChain, LlamaIndex, or custom toolchains. • Experience enabling DevOps practices across multiple teams or business units. • Agile delivery experience using Scrum, Kanban, or SAFe. Roles and Responsibilities: • You build things and share them — your coaching is your working code, your pipelines, your agents, and your reusable platform patterns. • You think in systems: you understand the downstream effects of cloud, identity, container, and automation decisions. • You're comfortable in ambiguity and can define the right problem before solving the wrong one. • You have strong opinions on automation, reliability, security, IAM, and operational simplicity — and can defend them with evidence. • You learn fast, experiment deliberately, and know when to stop experimenting and ship. • You understand that secure defaults, clear ownership, and good developer experience are essential to platform adoption.

Ce que vous ferez

Build and share reusable platform patterns, pipelines, and AI agents while ensuring operational simplicity. Design secure, scalable cloud systems and provide coaching through working code and automation.

Exigences

Requires 3-5+ years of experience in cloud platform engineering with strong proficiency in Python and AWS production workloads. Must have hands-on experience with containerization and the integration of AI/LLM-based tools in production environments.

Compétences indiquées

• Kubernetes · Souhaitée
• CI/CD · Souhaitée
• Docker · Souhaitée
• Amazon Web Services · Souhaitée
• Terraform · Souhaitée
• Git · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• AWS
• Python
• DevOps
• CI/CD
• Kubernetes
• Docker
• LLMOps
• Infrastructure as Code
• IAM
• Terraform
• AI/LLM Integration
• Git
• Amazon ECS
• Amazon EKS
• DevSecOps
• API Integration

Domaines d’emploi

• Software
• Technology
• Engineering
• Consulting
• Data & Analytics