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# Priniciple AI Engineer

- **Company:** SunRay Enterprise Inc
- **Location:** Columbus, OH, United States (Remote available)
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Continuous Integration, Github, Python (Programming Language), Regression Testing, Azure Machine Learning, SAP (Applications), Software Engineering, Data Streaming, TypeScript, Microsoft Power Automate, SAP Integration Solutions, Large Language Models, Multi-Agent Systems, Containerization, Bicep, Enterprise Integration, Integration Frameworks, Terraform
- **Published:** September 21, 2026
- **Apply:** https://www.dice.com/job-detail/68236c22-2195-4198-8e8e-cfc0190f3132

## About the Role

* 10+ years of software engineering; strong Python and/or TypeScript
 * Deep Azure expertise: infrastructure-as-code (Bicep or Terraform), networking, identity, container platforms, Azure AI services
 * Production LLM or agentic systems you personally built and ran end to end data flows, orchestration, deployment, evaluation, incident response be prepared to walk through the most recent one
 * Evaluation engineering: you design and build eval suites datasets, metrics, regression tests wired into CI and hold them as release gates, not demos
 * Ownership of CI/CD pipelines (GitHub Actions, Azure DevOps, or equivalent)
 * Identity-aware API and integration design
 * Sound judgment partnering with vendors while keeping core capability in-house
 * AI-augmented development as your default we work with Claude and Microsoft Copilot, and expect them in your daily build loop, * Model Context Protocol (MCP) implementation experience
 * SAP or other enterprise ERP integration exposure
 * Experience with enterprise integration/automation (iPaaS) platforms
 * Prior technical-lead or mentoring experience
 * Regulated or industrial-sector environments

## Description

* Implement SAP identity passthrough in partnership with the IT/SAP organization
 * Own CI/CD for AI assets, plus the evaluation and observability harness with cost and usage telemetry instrumented from day one
 * Ship the first production AI use case, then the prioritized portfolio: retrieval, grounding, and agentic workflows, released behind evaluation gates
 * Co-build alongside an enterprise integration partner during the initial platform build, internalizing patterns so the capability stays in-house
 * Define the function's engineering standards, tooling, and practices, and serve as technical lead as the team grows