The role involves managing and optimizing AWS infrastructure components such as EC2, VPC, Route 53, NAT Gateway, Auto Scaling, Kubernetes, and EKS to support generative AI solutions. This includes ensuring scalable and secure deployments using Terraform, n8n, and containerization tools like Docker.
Key Responsibilities
- Deploy large language models (LLMs) on AWS Bedrock using boto3 for scalable inference workloads.
- Manage SageMaker pipelines focused on LLM fine-tuning, leveraging EKS/ECS clusters and Auto Scaling for efficient resource utilization.
- Configure and maintain CI/CD pipelines using GitLab CI and Terraform to automate infrastructure and application deployments.
- Set up Retrieval-Augmented Generation (RAG) infrastructure with AWS OpenSearch and langchain within VPC environments to support AI workflows.
- Deploy AI agents such as crewai and autogen on AWS Lambda, integrating with n8n for workflow automation.
- Orchestrate containerized deployments using Docker on Amazon ECS/EKS, employing Kubernetes for cluster management.
- Manage networking components including Route 53 and NAT Gateway to ensure secure and reliable access to cloud resources.
- Monitor infrastructure health and performance using Amazon CloudWatch and Weights & Biases (wandb) tools.
Required Qualifications
- Minimum of 7 years of DevOps experience with a strong focus on AWS cloud services and AI-related workflows.
- Deep expertise in AWS services including Bedrock, SageMaker, EC2, VPC, Route 53, NAT Gateway, Auto Scaling, ECS, EKS, and boto3 SDK.
- Proficient in infrastructure as code and container orchestration technologies such as Terraform, Docker, and Kubernetes.
- Hands-on experience with CI/CD tools and pipelines, specifically CodePipeline, CodeBuild, and GitLab CI.
- Familiarity with AI workflow automation tools like langchain and n8n.
Preferred Qualifications and Benefits
- AWS certifications such as DevOps Engineer or Solutions Architect are highly desirable.
- Experience with llama-index and advanced n8n templates is a plus.
- Strong understanding of LLMs, AI workflows, and AWS cloud ecosystem enhances candidate suitability.
This position offers the opportunity to work at the intersection of cloud infrastructure and cutting-edge AI technologies, contributing to scalable and secure generative AI deployments.
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