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Automatically prepared from the listing. Check the original description for the full requirements.
Jump to the original descriptionResponsibilities
Design and operate production workloads on AWS using container platforms and infrastructure as code. Build and integrate AI/LLM-based tools and agents while ensuring security and reliability through LLMOps and DevSecOps practices.
Requirements
Requires 3-5+ years of experience in CI/CD and platform engineering with strong proficiency in Python and AWS. Candidates must have production experience with containers and a deep understanding of LLMOps and agent architectures.
Working hours
40 hours per week
Skills
- CI/CD
- Cloud Engineering
- Python
- AWS
- Docker
- Kubernetes
- LLMOps
- Infrastructure as Code
- DevSecOps
- Git
- API Integration
- Amazon ECS
- Amazon EKS
- AWS IAM
- Prompt Management
- Agent Architectures
Visa sponsorship
Not detected in the job text
Categories
- Software
- Technology
- Engineering
- Data & Analytics
- Administrative
Keywords
- CI/CD
- Cloud Engineering
- Python
- Java
- .NET
- Groovy
- Node.js
- AWS
- AWS IAM
- Docker
- Kubernetes
- Amazon ECS
- Amazon EKS
- AI
- LLM
- LLMOps
- Prompt Management
- Agent Architectures
- Git
- Infrastructure as Code
- DevSecOps
- Configuration Management
- Cloud-native
- API Integrations
- Production Scripting
- Observability
- Reliability
- Build Automation
- Release Pipelines
- Information Services
Original job description
Archived listing. The details below describe a past opening.
- 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
Closing date
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