[Remote] AI Platform Engineer

Note: The job is a remote job and is open to candidates in USA. Vallen Distribution is building a governed, production-grade AI capability on an Azure-first, Databricks-centered architecture. The AI Platform Engineer will own the Databricks AI/ML platform layer, establish enterprise AI governance, review shadow AI solutions, and deliver automation use cases with business teams.

Responsibilities

• Own the AI/ML layer on Databricks: feature stores, MLflow experiment tracking and model registry, and RAG/prompt architectural standards
• Define and enforce prompt engineering standards and LLM integration patterns across internal tools
• Partner with Data Engineering to design data pipelines that feed AI/ML use cases from the Unity Catalog lakehouse
• Evaluate and implement agentic frameworks (Claude API, Databricks AI agents) for internal automation
• Directly build and deliver 2–3 automation use cases per year with business teams (HR, Legal, customer service, operations)
• Own full delivery lifecycle: scoping, design, build, testing, and handoff to platform operations
• Produce well-documented, governed solutions — not one-off scripts
• Serve as the first-filter reviewer for all AI tools and platforms proposed for use at Vallen
• Partner with Security and Infrastructure to assess data classification risk, vendor posture, and integration risk before production deployment
• Review user-built solutions (Claude Desktop, Copilot, Cowork, and similar tools) and determine when a productivity workflow has crossed into enterprise scope — then lead the governed rebuild
• Maintain Vallen's enterprise AI acceptable use policy, data classification guardrails, and platform-tier standards
• Embed with departments to surface and prioritize automation opportunities
• Maintain a scored use case backlog; facilitate structured discovery sessions with business stakeholders
• Serve as the internal AI resource teams engage before going external

Skills

• Bachelor's degree in Computer Science, Information Technology, or a related field
• Experience in AI/ML engineering, data engineering, or a closely related technical role
• Hands-on experience with Databricks — MLflow, notebooks, Unity Catalog, and Python/SQL workflows; or equivalent lakehouse platform experience with demonstrated ability to ramp quickly
• Practical experience building with LLMs: prompt engineering, RAG pipelines, or API integration— production or project-level experience counts
• Strong Python skills; ability to own full solution delivery from prototype to production
• Solid grounding in Azure: Azure OpenAI, Azure Data Lake Storage, Azure Key Vault, and core networking/security concepts
• Demonstrated ability to work across technical and non-technical stakeholders — you can explain what you're building and why it matters
• Experience reviewing or documenting AI/ML solutions for risk, data sensitivity, or governance considerations
• Long periods of time working on a computer and performing repetitive key-boarding activities
• While performing the duties of this job, the employee is regularly required to talk and hear. The employee frequently is required to sit. The employee is occasionally required to stand and walk. The employee may be required to occasionally lift and/or move up to 10 pounds. Specific vision abilities required by this job include close vision, and ability to adjust focus
• Experience in distribution, supply chain, or industrial B2B environments
• Familiarity with agentic frameworks: Databricks AI Agent Framework, LangChain, AutoGen
• Exposure to enterprise AI governance concepts: acceptable use policies, data classification tiers, model risk review
• Experience with Azure DevOps (ADO), CI/CD pipelines)
• Familiarity with Power BI, Databricks Genie, or other BI/AI consumption layers
• Working knowledge of MDM, ERP data structures, or multi-system data environments

Benefits

• Remote work arrangement

Company Overview

Company H1B Sponsorship