AI Platform Engineer

About the role

We are looking for an experienced AI Platform Engineer to design, build, and operate a shared AI platform that serves as the foundation for all AI initiatives across the organization. You will ensure that teams can deploy models and agents quickly without reinventing core infrastructure.

Key responsibilities

• Build and maintain shared AI platform infrastructure, including compute provisioning, networking, and IAM for AI workloads.
• Own internal tooling and templates that enable consistent model/agent deployment.
• Standardize CI/CD pipelines for AI workloads and manage shared evaluation platforms.
• Handle platform‑level cost governance, capacity planning, and security posture in partnership with AI Security Engineers.
• Collaborate with MLOps/LLMOps engineers at the platform‑workload boundary.
• Balance competing infrastructure requests from multiple practice leads and document capabilities for self‑service.
• Forecast and justify platform spend to non‑technical leadership.

Required profile

• 6–12+ years of platform/infrastructure engineering experience, with at least 2 years supporting AI/ML workloads.
• Deep expertise in cloud infrastructure (IaC, Kubernetes, networking, IAM) and experience with vector/graph databases.
• Proven track record building internal developer platforms and tooling.
• Experience integrating managed AI services (Azure AI Foundry, AWS Bedrock, Google Vertex AI) alongside open‑source stacks.
• Strong knowledge of multi‑tenant capacity planning, cost allocation, and platform security hardening.
• Excellent stakeholder management across multiple practice leads.

Required skills

• Infrastructure as Code (IaC)
• Kubernetes
• Cloud networking
• Identity and Access Management (IAM)
• Vector and graph databases
• Azure AI Foundry
• AWS Bedrock
• Google Vertex AI
• MLOps / LLMOps tooling
• Platform security hardening