Associate AI Engineer
On-siteMcKinney, Texas, United States
Job Summary
Develop bounded AI and automation capabilities using Microsoft Fabric, SQL, and APIs to translate approved backlog items into measurable releases. Partner with business owners and subject-matter experts to define requirements, explain tradeoffs, and support adoption through training materials. Contribute to the enterprise ontology and knowledge foundation by documenting objects, relationships, and semantic models while preserving source permissions. Conduct design reviews with the Principal Solutions Architect, create prototypes, and carry approved designs through to release. Document architecture, tests, and runbooks to ensure maintainability, then evaluate accuracy, failure modes, and cost to propose clear release recommendations.
Required Qualifications
- 0-3 years' professional experience in software development, data engineering or a related technical role
- Bachelor's degree in computer science, software engineering, information systems, data science or a related field, or commensurate experience
- Able to write & troubleshoot code in VS Code
- Working knowledge of SQL
- Working understanding of REST APIs, Git-based collaboration, testing & basic cloud concepts
- Secure handling of credentials & data
- Able to explain a technical project, the decisions personally made, the tradeoffs & how the result was validated
- Clear written communication
- Able to relate to & communicate with a diverse group of professionals
- Ability to work individually & as part of a team
- Self-motivated & driven
- Highly organized & detail oriented
- Highly analytical thinker
- Internal & external customer service
- Willingness to ask for context when requirements are incomplete
- Minimum 20 hrs of Continued Education (yearly)
Desired Qualifications
- Microsoft Azure or Fabric, OneLake or lakehouse patterns, Power BI, Azure AI Search, Azure OpenAI or Azure AI Foundry
- LLM applications, RAG, embeddings, evaluation, prompt or model lifecycle management, agents or workflow automation
- Coursework or project work in knowledge representation, semantic modeling, enterprise ontologies or knowledge graphs including Protégé, OWL, RDF or SPARQL
- Metadata, data lineage, document management or construction & project-control systems
- TypeScript, C# or another modern language
- CI/CD, containerized services, monitoring, cost management or secure enterprise integration
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