Senior Azure AI Engineer

Compunnel

• $130K — $155K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years of software engineering experience with strong Python and/or TypeScript skills.
  • Deep Azure proficiency, including Infrastructure-as-Code with Bicep or Terraform.
  • Hands-on experience with building and operating production LLM or agentic AI systems.
  • Strong evaluation engineering background, designing metrics, suites, and regression tests integrated into CI pipelines.
  • Experience with CI/CD pipelines using GitHub Actions, Azure DevOps, or similar.
  • Capability to design identity-aware APIs and integrations.
  • Familiarity with AI-assisted development tools like Claude and Microsoft Copilot.

Responsibilities

  • Build and operate a governed enterprise MCP gateway and Azure AI environments.
  • Implement SAP identity passthrough in collaboration with IT teams.
  • Own and establish CI/CD for AI assets, focusing on evaluation and observability.
  • Develop and deploy production AI use cases, enhancing retrieval and grounding workflows.
  • Establish evaluation gates for the release of production AI solutions.
  • Collaborate with integration partners to develop reusable technical patterns.
  • Define engineering standards, practices, and testing methods for deployment.
  • Provide mentorship and technical leadership as the engineering team matures.
  • Support production applications, ensuring operational performance and reliability.

Benefits

  • Opportunity to work on cutting-edge AI technology in a principal engineering role.
  • Engage in hands-on architecture and production-level work.
  • Be part of a collaborative environment with integration partners.
  • Lead the development of scalable engineering practices for AI.
  • Potential for professional growth through technical leadership and mentorship.
Full Job Description
Job Summary: Seeking a Senior Azure AI Engineer to build and operate an enterprise AI platform and production AI applications end to end. This principal-level, hands-on role spans infrastructure, AI orchestration, application development, evaluation, observability, and production operations. The ideal candidate will establish engineering standards, deliver production AI solutions, and take ownership of the systems they build throughout their lifecycle. 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 capability grows. • Support production applications and take ownership of operational performance, reliability, and incident response. • Establish scalable engineering practices for 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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