Cloud Platform Engineer – AWS, Python, DevOps & AI/LLM
Posted
Summary
This engineer builds and operates AWS-based developer platform infrastructure: Python automation, CI/CD pipelines, containers (Docker/Kubernetes/ECS/EKS), IAM, and infrastructure-as-code, plus integrating AI/LLM agents into production tooling. It suits a platform/DevOps engineer with a DevSecOps mindset and LLMOps experience.
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.
Skills
- Agentic AI
- Agile
- AI
- API
- Authentication
- Automation
- AWS
- CDK
- CI/CD
- Cloud
- Cloud Native
- CloudFormation
- CloudWatch
- Developer Experience
- DevOps
- DevSecOps
- Docker
- .NET
- ECS
- EKS
- Git
- Groovy
- Helm
- IAM
- Infrastructure as Code
- Java
- Kanban
- Kubernetes
- Lambda
- LangChain
- LlamaIndex
- LLM
- LLMOps
- Networking
- Node.js
- Observability
- Python
- S3
- Scrum
- Terraform
- VPC