Director, Enterprise AI & Databricks Platforms (GenAI / Microsoft AI)

Hybrid - Build, lead a new enterprise AI function from the ground up—owning GenAI, RAG, agentic systems, and automation on a modern Databricks + Microsoft stack. This Jobot Job is hosted by: Liz Valdez Are you a fit? Easy Apply now by clicking the "Quick Apply" buttonand sending us your resume. Salary: $180,000 - $250,000 per year A bit about us: We’re a growing, innovation-focused organization investing heavily in enterprise data and AI capabilities. Our technology environment is centered around a modern data platform, and we’re now scaling advanced AI solutions, including generative AI, multi-agent systems, and intelligent automation to drive measurable business outcomes. This is not a research role, this is about operationalizing AI at scale. Why join us? Greenfield opportunity to build enterprise AI capability from scratch High ownership role spanning architecture, execution, and early team leadership Direct impact on operational efficiency (supply chain + business automation use cases) Modern AI stack centered on Databricks + Microsoft Copilot ecosystem Visible role working directly with senior leadership Comprehensive benefits including medical/dental/vision, 401(k) with profit sharing, tuition reimbursement, and flexible spending programs. Job Details Director of AI / Generative AI Platform (Greenfield Build) We are launching a greenfield enterprise AI platform focused on building and deploying Generative AI, agent-based systems, and intelligent automation into real production environments. This is a founding-level leadership role responsible for standing up the AI function from the ground up. You will serve as both architect and hands-on builder, defining the platform, delivering early production use cases, and scaling a new AI engineering organization over time. This is a builder-first role in a new function - you will be directly responsible for building and shipping production AI systems. What You’ll Do Architect and deliver a greenfield enterprise AI platform Design and deploy production-grade RAG, LLM, and agent-based systems Build and operationalize AI use cases tied to real business impact (e.g., supply chain, operations, automation) Stand up and scale an initial AI engineering team (~3 engineers) Define enterprise AI architecture using Databricks + Microsoft ecosystem Own end-to-end AI delivery: architecture → development → deployment → iteration Drive adoption of Copilot, RPA, and intelligent automation across the enterprise Partner with business stakeholders to translate operational challenges into AI solutions Must-Have Skills Enterprise AI / Generative AI architecture with hands-on production build experience Proven experience building and deploying LLM, RAG, or agent-based systems in production Strong ability to design end-to-end AI systems (architecture + implementation) Experience with Databricks + MLflow (or equivalent AI platforms) Experience building or scaling AI engineering teams Strong technical depth—this is a builder-first role, not strategy-only Required Experience 10+ years in artificial intelligence, machine learning, automation, or related technical fields Demonstrated experience designing and deploying AI/ML or Generative AI systems in production environments Experience owning technical delivery of AI systems and leading AI/ML engineering execution (hands-on leadership) Preferred Experience 12–15+ years of progressive experience across AI engineering, ML engineering, intelligent automation, or enterprise data platforms Experience building or contributing to enterprise AI platforms or greenfield AI initiatives Hands-on experience with modern AI ecosystems such as: Databricks (MLflow, model serving, vector search) Microsoft AI stack (Azure ML, Copilot, Power Automate) Experience delivering AI-driven solutions tied to measurable business outcomes (automation, operational efficiency, decision support) Nice-to-Have Agentic AI / multi-agent systems (LangChain, LangGraph, AutoGen) Microsoft Copilot integration experience Power Automate / RPA exposure Supply chain, logistics, or enterprise operations AI use cases Vector databases / embeddings (Pinecone, Weaviate, FAISS) ERP / CRM AI integrations (SAP, Salesforce, Dynamics) Interested in hearing more? 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