Principal AI Engineer

Job Summary


The Principal AI Engineer will be the founding engineer responsible for building and operating the enterprise AI platform and its first production applications end-to-end. This role sets the engineering standards - repository structure, testing, deployment patterns - that future hires will build upon. It is a principal-scope, hands-on role where you ship code weekly and own it in production.


Key Responsibilities

1. Bu ild and operate AI environments including the governed enterprise MCP gateway and Azure AI foundation.
2. Implement SAP identity passthrough in partnership with IT/SAP teams.
3. Own CI/CD pipelines for AI assets, with evaluation and observability harness instrumented from day one.
4. Ship production AI use cases including retrieval, grounding, and agentic workflows released behind evaluation gates.
5. Co-build with integration partners during initial platform build, internalizing patterns for long-term capability.
6. Define engineering standards, tooling, and practices, serving as technical lead as the team grows.
7. First 90 Days
8. Deliver the MCP gateway carrying production traffic for the first use case in a company-owned Azure environment.
9. Establish evaluation scores and telemetry flowing from day-one instrumentation.
10. Publish engineering standards for repository structure, testing, and deployment.

Required Qualifications

1. 10+ years of software engineering experience.
2. Strong coding fluency in Python and/or TypeScript.
3. Deep Azure expertise: infrastructure-as-code (Bicep/Terraform), networking, identity, container platforms, Azure AI services.
4. Hands-on experience building and operating production LLM/agentic systems end-to-end (data flows, orchestration, deployment, evaluation, incident response).
5. Expertise in evaluation engineering: designing eval suites, datasets, metrics, regression tests wired into CI/CD.
6. Ownership of CI/CD pipelines (GitHub Actions, Azure DevOps, or equivalent).
7. Identity-aware API and integration design.
8. Sound judgment in vendor partnerships while keeping core capability in-house.
9. Daily use of AI assistants (Claude, Microsoft Copilot) in development workflows.

Preferred Qualifications

1. Exper ience implementing Model Context Protocol (MCP).
2. Exposure to SAP ERP integration or other enterprise ERP systems.
3. Experience with enterprise integration/automation (iPaaS) platforms.
4. Prior technical-lead or mentoring experience.