AI Engineer

This position is hybrid working from our Legacy West Support Center located in Plano, Texas

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, including tooling for marketing, supply chain, and retail operations.

• 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 across all AI services.

• Partner with security and infrastructure teams to ensure AI systems comply with Zero Trust principles, data privacy requirements, and enterprise identity standards via Entra ID and Azure Key Vault.

• Contribute to internal AI sandbox environments, enabling both professional and citizen developers to experiment with generative AI tools safely and within governance guardrails.

• Hands-on experience building production LLM applications with structured outputs, tool/function calling, and multi-agent orchestration patterns.

• Familiarity with Model Context Protocol (MCP) server design patterns and building context-aware AI tool integrations.

• Prior experience in retail, CPG, or large-scale enterprise environments where AI outcomes directly impact store operations or customer experience.

• Understanding of responsible AI frameworks, AI risk management, and enterprise AI SDLC governance practices including audit trails and policy enforcement.

• Passionate Learner – inquisitive about the business; open to feedback and coaching, applies learning quickly; applies learning to improve processes and procedures, proactively shares learning with colleagues and leaders; realigning and reshaping projects

• Flexible & Agile Adapter – responsive and open to change; works well with ambiguity; adapts to new plans or directions; keeps calm under pressure; perseveres to achieve the plan/task; doesn’t dwell on the past

• Talent Builder – considers how we can create an inclusive culture; encourages input from others; invests time as an informal/formal coach or buddy; works to build a diverse team with the right skills and knowledge; looks for ways to acknowledge, motivate, and value the team

• Effective Communicator – articulates in an appropriate and accurate manner; emotionally astute while remaining authentic to own style/self; encourages others to express views and opinions; demonstrates active listening and uses probing questions; is concise and relevant with data/info

• Team Builder – references the importance of teamwork and actively demonstrates collaboration and sharing; builds and/or participates in effective teams; values the importance of inclusion and various sources of thought/input; humble when operating within a team