AI Engineer
This position is hybrid working from our Legacy West Support Center located in Plano, Texas
About Sally Beauty Holdings, Inc.
At SBH, our purpose is to inspire a more colorful, confident, and welcoming world. We are the leader in professional hair color, selling and distributing professional beauty supplies across 11 countries through our Sally Beauty and Beauty Systems Group businesses.
About The Role
You will work within our enterprise AI governance framework—collaborating with business stakeholders, data engineers, and platform teams—to deliver scalable, secure, and production-ready AI applications. From LLM-powered workflows to agentic automation pipelines, you will play a pivotal role in shaping how Sally Beauty leverages generative AI.
Responsibilities
- Design, develop, and deploy AI/ML models and generative AI solutions into production environments using Azure AI Foundry, Azure OpenAI, and AKS-based microservice architectures.
- Build and maintain LLM-powered applications including prompt engineering frameworks, RAG pipelines, agent orchestration, and MCP (Model Context Protocol) server integrations.
- Collaborate with stakeholders to translate business requirements into AI proof-of-concept (POC) builds and production-ready features.
- Develop and maintain CI/CD pipelines for AI workloads using GitHub Actions and ArgoCD, adhering to enterprise AI governance, security, and SDLC standards.
- Implement responsible AI practices including model evaluation, bias detection, hallucination mitigation, observability, and audit logging.
- Partner with security and infrastructure teams to ensure AI systems comply with Zero Trust principles and data privacy requirements.
- Contribute to internal AI sandbox environments, enabling both professional and citizen developers to experiment with generative AI tools safely.
- Document AI solution architectures, API contracts, and integration patterns; present findings to cross-functional teams and leadership.
Knowledge, Skills & Abilities Requirements
- 3 years in software engineering or data science, with at least 1 year in AI/ML engineering or applied generative AI development.
- Bachelor's degree in computer science, Data Science, Engineering, or a related technical field required.
- Proficiency in designing and deploying LLM-powered solutions including fine-tuning, prompt engineering, retrieval-augmented generation (RAG), and agentic frameworks such as LangChain, AutoGen, or CrewAI.
- Hands-on experience with Azure AI Foundry, Azure OpenAI Service, and AKS-based deployments.
- Strong programming skills in Python including FastAPI, Pydantic, and asyncio.
- Working knowledge of vector databases such as Qdrant, pgvector, or Weaviate.
- Experience with model evaluation, A/B testing, and drift detection.
- Solid understanding of CI/CD practices using GitHub Actions and ArgoCD.
Preferred Qualifications
- Hands-on experience building production LLM applications with structured outputs, tool/function calling, and multi-agent orchestration.
- Familiarity with Model Context Protocol (MCP) server design patterns.
- Prior experience in retail, CPG, or large-scale enterprise environments.
- Understanding of responsible AI frameworks, AI risk management, and enterprise AI SDLC governance.
- Experience with AI-assisted developer tooling such as Claude Code, GitHub Copilot, Cursor, or Gemini CLI.
Working Conditions & Physical Requirements
This will be a hybrid role required to be onsite at the Corporate office on specified days. The work is sedentary; however, occasional travel to company locations may be required.