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AI Infrastructure DevOps Engineer

Shrinq Consulting Group — United States · Posted ~1 day ago

Skills

DevOps AI Infrastructure AWS Azure GCP Docker Kubernetes Terraform Infrastructure as Code CI/CD Vector Databases RAG Cloud Security Cost Optimization OpenTofu CloudFormation LangChain LlamaIndex Semantic Kernel Pinecone Milvus Qdrant pgvector PostgreSQL GitHub Actions GitLab CI Jenkins

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Summary

A specialized DevOps engineering role focused on infrastructure for modern AI applications. You will architect secure cloud-native environments, optimize vector databases and RAG workloads, manage containerized systems, control high-performance compute costs, and build automated CI/CD pipelines for software and AI model deployment.

Highlights

Specialized DevOps opportunity at the intersection of AI and cloud infrastructure. The role covers scalable secure infrastructure, vector databases, RAG pipelines, GPU/TPU cost optimization, container orchestration, Infrastructure as Code, and automated model deployment.

Description

Implement and manage infrastructure for AI orchestration frameworks (e.g., Lang Chain, Llama Index, Semantic Kernel). Optimize vector databases (e.g., Pinecone, Milvus, Qdrant, or pgvector in Postgre SQL) for highly efficient Retrieval-Augmented Generation (RAG) pipelines. Implement cost-optimization strategies for heavy compute resources (GPUs/TPUs). Architect, scale, and maintain secure, cloud-native infrastructure utilizing AWS, Azure, or GCP. Orchestrate and manage containerized workloads using Docker and Kubernetes. Implement robust Infrastructure as Code (Ia C) using Terraform, Open Tofu, or Cloud Formation. Build, maintain, and optimize secure CI/CD pipelines (Git Hub Actions, Git Lab CI, or Jenkins) for automated software and model deployment.