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 multiple AI practices. You will create the foundational infrastructure that enables teams to deploy models and agents efficiently without reinventing deployment plumbing.

Key responsibilities

• Build and maintain shared AI platform infrastructure, including compute provisioning, networking, and IAM for AI workloads.
• Own internal tooling and templates that standardize model/agent deployment across practices.
• Standardize CI/CD pipelines for AI workloads and manage shared AI evaluation platforms.
• Manage platform‑level cost governance, capacity planning, and security posture in partnership with AI Security Engineers.
• Collaborate with MLOps/LLMOps engineers on the interface between platform and workload‑specific operations.
• Balance competing infrastructure requests from multiple practice leads and document platform 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, and IAM.
• Proven experience building internal developer platforms and tooling.
• Ability to manage multi‑tenant capacity planning, cost allocation, and platform security hardening.
• Strong stakeholder management across multiple practice leads.

Required skills

• Infrastructure as Code (IaC)
• Kubernetes
• Networking
• Identity and Access Management (IAM)
• Vector and graph databases
• Microsoft Azure AI Foundry
• AWS Bedrock
• Google Vertex AI