Director, Cloud AI Platform Engineering

Location: Chicago; hybrid workstyle aligned to an hirify.global office, with travel to client sites up to 25%

Salary: $134,000–$269,000 per year, plus discretionary bonus

Company

Professional services and managed cloud infrastructure provider serving middle-market companies globally, including clients with $200M–$4B in revenue.

What you will do

• Design and deploy AI landing zones on Azure and AWS, including networking, identity, policy, logging, and private endpoints.
• Deploy model platforms using Azure AI Foundry, Azure OpenAI, Amazon Bedrock, and SageMaker, integrating commercial and open-weight models.
• Build infrastructure for RAG and agent systems, including vector stores, orchestration, MCP servers, and API gateways.
• Codify infrastructure with Terraform or Bicep and deliver it through CI/CD pipelines.
• Take prototype and vibe-coded AI applications to production by adding containers, authentication, secrets management, testing, observability, and security guardrails.
• Run LLMOps and FinOps, advise CIOs, CISOs, and engineering leads, and transition platforms into managed services with runbooks, SLAs, and operational handoffs.

Requirements

• 5+ years of experience in cloud, platform, or DevOps engineering and 1+ year deploying generative AI workloads in production.
• Hands-on expertise in Azure or AWS, with working knowledge of the other platform.
• Infrastructure as code using Terraform or Bicep and CI/CD using GitHub Actions or Azure DevOps.
• Experience with Docker, Kubernetes including AKS or EKS, or serverless equivalents.
• Python plus either TypeScript or Go.
• Cloud identity and security experience with Entra ID or IAM, Key Vault or Secrets Manager, and private networking.
• Observability experience with Azure Monitor, CloudWatch, Datadog, or OpenTelemetry.
• Client-facing experience in consulting or a managed services provider.
• Ability to travel to client sites up to 25%.

Nice to have

• Bachelor's degree in a technical field or equivalent experience.
• Certifications including Azure AI Engineer Associate, Azure Solutions Architect Expert, AWS Certified Machine Learning or GenAI Developer, HashiCorp Terraform Associate, or FinOps Certified Practitioner.
• Experience with AI gateways and LLMOps tools such as Azure API Management AI gateway, LiteLLM, LangSmith, Langfuse, or MLflow.
• Experience with Semantic Kernel, LangGraph, Bedrock Agents, or MCP.
• Experience with Microsoft 365 Copilot, Copilot Studio, and Purview data governance.
• GPU capacity planning, cost management, mid-market clients, or PE-backed portfolio companies.

Culture & Benefits

• Hybrid work combining office presence and flexibility according to client, team, development, and relationship-building needs.
• Competitive benefits and compensation package.
• Work may be carried into managed AI and managed cloud services, including forward-deployed assignments with client IT teams.
• Equal employment opportunity and reasonable accommodation are provided.