Summary
✨ AI‑Generated
An AI infrastructure engineering role focused on designing cloud platforms for AI workloads, integrating services, and ensuring secure, reliable operations.
Highlights
Opportunity to build and optimize AI platforms, support machine learning workloads, and improve enterprise technology capabilities.
Description
AI Platform Engineer Overview
The AI Platform Engineer will design, build, and support Azure platforms powering AI and ML workloads, including generative AI and enterprise assistant tools.Collaborate on broader cloud infrastructure deployments, including networking, application hosting, and shared cloud services, ensuring robust and scalable solutions.Contribute to the integration and governance of enterprise AI tools, optimizing their functionality and ensuring compliance with organizational policies.Provide third-level technical support for AI projects, ensuring timely problem resolution and maintaining system reliability in a 24x7 environment.Monitor platform health, cost, and performance, implementing optimizations for GPU/CPU compute efficiency and cost-effectiveness.Develop and maintain accurate diagrams, configurations, and operating procedures for AI platforms, ensuring operational excellence.Integrate third-party AI APIs and multi-cloud AI services, enhancing platform capabilities and expanding service offerings.Establish responsible AI guardrails and troubleshoot platform incidents, ensuring ethical and secure AI operations.AI Platform Engineer Key Responsibilities & Duties
Design and maintain Azure AI/ML infrastructure, including AI Foundry, Azure OpenAI, Azure ML, Databricks, and Microsoft Fabric.Containerize and orchestrate workloads on AKS, managing MLOps/LLMOps CI/CD pipelines effectively.Support configuration and governance of enterprise AI tools, including Microsoft Copilot and Claude Cowork, ensuring optimal functionality.Implement infrastructure-as-code, managed identity, networking, and security for AI workloads and production models.Develop RAG pipelines, vector search, and LLM orchestration frameworks, enhancing AI application capabilities.Monitor and optimize platform health, cost, and performance, ensuring efficient resource utilization.Integrate third-party AI APIs and multi-cloud services, expanding platform functionalities.Maintain accurate documentation for AI platforms, ensuring operational clarity and support readiness.Provide technical support for AI projects, ensuring system reliability and timely issue resolution.AI Platform Engineer Job Requirements
Bachelor of Science in a relevant field with 3+ years of cloud/platform engineering experience.Strong expertise in Azure OpenAI, AI Foundry, Azure ML, Databricks, and Microsoft Fabric.Proficiency in Docker, Kubernetes (AKS), Python, and infrastructure-as-code tools like Terraform or Bicep.Experience with Azure networking, security fundamentals, and integrating REST-based AI services.Knowledge of RAG pipelines, vector search, LLM orchestration frameworks, and Kubernetes observability tools.Relevant certifications such as AZ-305/400/104, AI-102, DP-100/600, Databricks, AWS/GCP ML, CKA/CKAD.Excellent interpersonal, written, verbal, and time management skills, with a collaborative team-oriented approach.Experience with responsible AI/content safety tooling and FinOps cost optimization strategies.
