AI Platform Engineer

GENERAL SUMMARY

Under the direction of the Senior Cloud & Enterprise Architecture Manager, the AI Platform Engineer is responsible for the design, build, and support of the firm’s Azure platforms that powers our AI and ML workloads — generative AI, LLM apps, along with the integration of enterprise AI assistant/agent tools such as Microsoft Copilot and Claude Cowork as they're adopted across the business. Beyond AI-specific systems, this role will also contribute to broader non-AI cloud infrastructure deployments and buildouts — such as core networking, general application hosting, data platforms, and shared cloud services — making this a great fit for someone who wants a mix of AI-focused platform work and general cloud infrastructure engineering. This is a hands-on engineering role at the intersection of cloud infrastructure, MLOps, and applied AI.

Responsibilities include providing third level technical support for all AI based projects including design, and maintenance, troubleshooting, system monitoring and alerting and timely problem resolution for the firm’s 24x7 environment.

PRINCIPAL DUTIES AND TECHNICAL SKILLS

·       Expertise designing and maintaining Azure AI/ML infrastructure: AI Foundry, Azure OpenAI, Azure ML, Databricks, and Microsoft Fabric. Containerize and orchestrate workloads on AKS; own MLOps/LLMOps CI/CD pipelines.

·       Support the configuration and governance of enterprise AI assistant/agent tools such as Microsoft Copilot (M365 Copilot, GitHub Copilot), Copilot Coworker, and Claude Cowork, including access management, data connectors, and usage policies.

·       In-depth experience implementing and architecting infrastructure-as-code and managed identity, networking, and security for AI workloads, production models and LLM apps, RAG pipelines and vector search (Azure AI Search, Cosmos DB).

·       Cost Optimization & Performance - Monitor platform health, cost, and performance; optimize GPU/CPU compute spend.

·       Integrate and evaluate third-party AI APIs (Anthropic, OpenAI, Gemini) and multi-   cloud AI services.

·       Contribute to broader cloud infrastructure: landing zones, networking, shared platform services. Maintain accurate diagrams, configurations, and operating procedures for all AI Platforms. 

·       Provide support for all AI based projects including equipment installation, upgrade, maintenance, troubleshooting, system monitoring and alerting and timely problem resolution. Establish responsible AI guardrails and troubleshoot platform incidents.