About this role
Vallen Distribution seeks a hands-on AI Platform Engineer to build a governed, production-grade AI capability on an Azure-first, Databricks-centered architecture. The engineer will own the Databricks AI/ML platform layer, set enterprise AI standards, review ungoverned solutions and deliver automation with business teams. The role works directly with the SVP of Data & Technology Innovation.
Responsibilities
- Own feature stores, MLflow experiment tracking and model registry, and RAG and prompt architecture standards. Define LLM integration patterns, partner with Data Engineering on Unity Catalog lakehouse pipelines, and evaluate agentic frameworks for internal automation.
- Build 2–3 automation use cases per year with teams such as HR, Legal, customer service and operations. Manage scoping, design, build, testing, documentation and handoff to platform operations.
- Review proposed AI tools and user-built solutions. With Security and Infrastructure, assess data classification, vendor and integration risks before production deployment; lead governed rebuilds when workflows reach enterprise scope. Maintain acceptable-use policies, data guardrails and platform-tier standards.
- Work with departments to discover and prioritize opportunities, maintain a scored use-case backlog and facilitate stakeholder discovery sessions.
Required qualifications
A bachelor's degree in Computer Science, Information Technology or a related field; experience in AI/ML engineering, data engineering or a closely related role; hands-on Databricks experience with MLflow, notebooks, Unity Catalog and Python/SQL workflows, or equivalent lakehouse experience with the ability to ramp quickly. Candidates need practical LLM-building experience through prompt engineering, RAG pipelines or API integration; strong Python skills; the ability to deliver solutions from prototype to production; grounding in Azure OpenAI, Azure Data Lake Storage, Azure Key Vault and networking/security concepts; stakeholder communication skills; and experience reviewing or documenting AI/ML risk, data sensitivity or governance. Production or project-level LLM experience counts.
Preferred
Distribution, supply chain or industrial B2B experience; familiarity with the Databricks AI Agent Framework, LangChain or AutoGen; enterprise AI governance; Azure DevOps and CI/CD; Power BI or Databricks Genie; and MDM, ERP or multi-system data environments.
The posting lists Belmont, North Carolina and Houston, Texas, and includes a remote-work tag. It specifies 40 hours per week. Benefits include medical, dental and vision coverage; a 401(k) with discretionary match; life and disability insurance; parental leave; flexible spending accounts; paid time off and holidays; tuition reimbursement; and an employee assistance program.