Principal AI Platform Engineer – Agentic AI & MCP

Job Description

We are seeking a Principal AI Platform Engineer to serve as a founding engineer responsible for building and operating an enterprise AI platform and production-grade Agentic AI applications. This is a hands-on principal-level role where you will own the platform end-to-end, from Azure infrastructure and orchestration through evaluation, CI/CD, observability, and production operations.

You will establish the engineering standards, architecture, tooling, and development practices that will serve as the foundation for the growing AI engineering organization.

Key Responsibilities

• Build and operate a governed Model Context Protocol (MCP) gateway and Azure AI environments.

• Design and implement secure SAP identity passthrough and enterprise API integrations.

• Build and own CI/CD pipelines for AI applications, models, and platform assets.

• Develop AI evaluation frameworks including datasets, metrics, regression testing, and automated release gates.

• Implement observability, telemetry, cost tracking, usage monitoring, and production diagnostics.

• Build and deploy production LLM, RAG, and Agentic AI applications.

• Own the first production AI use case and expand the platform to support retrieval, grounding, and agentic workflows.

• Partner with enterprise integration teams while ensuring core AI platform capabilities remain in-house.

• Establish engineering standards for repository structure, testing, deployment, security, and operational practices.

• Provide technical leadership and mentoring as the AI engineering team grows.

Required Qualifications

• 10+ years of software engineering experience.

• Strong Python and/or TypeScript development experience.

• Deep experience with Microsoft Azure, including:

  • Azure AI services

  • Azure networking and identity

  • Container platforms

  • Infrastructure as Code using Terraform or Bicep

• Hands-on experience building and operating production LLM or Agentic AI systems end-to-end.

• Strong experience with RAG, retrieval, grounding, LLM orchestration, and AI agents.

• Experience designing and implementing AI evaluation frameworks, including datasets, evaluation metrics, regression testing, and CI/CD release gates.

• Strong CI/CD experience with GitHub Actions, Azure DevOps, or equivalent.

• Experience designing identity-aware APIs and enterprise integrations.

• Strong understanding of production software engineering, testing, deployment, monitoring, and incident response.

• Experience using AI-assisted development tools such as Claude, Microsoft Copilot, or similar tools.

Preferred Qualifications

• Hands-on Model Context Protocol (MCP) implementation experience.

• SAP / ERP integration experience.

• Experience with enterprise integration or iPaaS platforms.

• Previous experience as a Technical Lead, Principal Engineer, or Engineering Lead.

• Experience working in regulated, manufacturing, industrial, or enterprise environments.

• Experience with Azure OpenAI / Azure AI Foundry or related Azure AI technologies.

What You'll Accomplish in Your First 90 Days

• Establish the AI platform and MCP gateway in the enterprise Azure environment.

• Support production traffic for the first AI use case.

• Implement evaluation, observability, cost, and usage telemetry.

• Establish engineering standards, development practices, and deployment patterns for the future AI engineering team.