Ai Platform Engineer

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 24×7 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.