AI Architecture & Engineering AI Transformation/ Principal AI Engineer

Compunnel

• $138K — $165K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years of software engineering experience with strong Python and/or TypeScript expertise.
  • Deep expertise in Azure, including Infrastructure-as-Code using Bicep or Terraform.
  • Hands-on experience with production LLM or agentic AI systems end to end.
  • Proficient in AI data flows, orchestration, deployment, and monitoring.
  • Strong experience in designing evaluation suites, datasets, and regression tests for CI pipelines.
  • Experience managing CI/CD pipelines using GitHub Actions, Azure DevOps, or similar tools.
  • Proven ability to partner with vendors while managing core technical capabilities.

Responsibilities

  • Build and operate an enterprise MCP gateway and Azure AI environments.
  • Implement SAP identity passthrough in collaboration with enterprise technology teams.
  • Own CI/CD processes for AI assets and establish evaluation and observability capabilities.
  • Develop and deploy production AI use cases, including retrieval and agentic workflows.
  • Establish evaluation gates for production AI releases.
  • Collaborate with enterprise integration partners on platform development.
  • Define engineering standards and technical practices for the team.
  • Provide technical leadership and mentorship as the team expands.
  • Support operational performance and reliability of production applications.

Benefits

  • Professional development opportunities and continuous learning.
  • Mentorship and technical leadership engagement.
  • Dynamic and supportive work environment fostering innovation.
  • Collaboration with diverse teams and cutting-edge technologies.
Full Job Description
Job Summary:
Seeking a Principal AI Engineer to build and operate an enterprise AI platform and production AI applications end to end. This role spans infrastructure, orchestration, application development, evaluation, observability, and production operations. The ideal candidate will establish engineering standards and remain deeply hands-on, delivering production AI solutions while providing technical leadership as the AI engineering capability grows.

Key Responsibilities:
• Build and operate a governed enterprise MCP gateway and Azure AI environments.
• Implement SAP identity passthrough in partnership with enterprise technology teams.
• Own CI/CD for AI assets and establish evaluation and observability capabilities with cost and usage telemetry.
• Develop and deploy production AI use cases involving retrieval, grounding, and agentic workflows.
• Establish evaluation gates for production AI releases.
• Collaborate with enterprise integration partners during initial platform development and internalize reusable technical patterns.
• Define engineering standards, tooling, repository structures, testing practices, and deployment patterns.
• Provide technical leadership and mentorship as the engineering team grows.
• Support production applications and take ownership of operational performance and reliability.
• Establish engineering practices that support scalable enterprise AI development.

Required Qualifications:
• 10+ years of software engineering experience with strong Python and/or TypeScript expertise.
• Deep Azure expertise, including Infrastructure-as-Code using Bicep or Terraform, networking, identity, container platforms, and Azure AI services.
• Hands-on experience building and operating production LLM or agentic AI systems end to end.
• Experience with AI data flows, orchestration, deployment, evaluation, monitoring, and incident response.
• Strong evaluation engineering experience, including designing evaluation suites, datasets, metrics, and regression tests integrated into CI pipelines.
• Experience owning CI/CD pipelines using GitHub Actions, Azure DevOps, or equivalent technologies.
• Experience with identity-aware API and integration design.
• Strong ability to partner with vendors while maintaining ownership of core technical capabilities.
• Experience using AI-assisted development tools such as Claude and Microsoft Copilot as part of daily engineering workflows.

Preferred Qualifications:
• Experience implementing Model Context Protocol (MCP).
• SAP or other enterprise ERP integration experience.
• Experience with enterprise integration and automation platforms.
• Prior technical leadership or mentoring experience.

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