Director of AI / ML Platform (Enterprise Databricks AI)

Jobot
Coppell, TX, United States
30 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Compensation
$180,000.0 - $250,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Audit Trail Data Architecture Information Engineering Machine Learning Role-Based Access Control Azure Machine Learning Search Technologies Enterprise Data Management Feature Engineering Microsoft Power Automate Large Language Models
+7 more
Generative AI Build Management Data Lakes AI Platforms Machine Learning Operations Virtual Agents Databricks

Job description

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., Director of AI / ML Platform (Enterprise Databricks AI)

We’re building the next generation of enterprise AI capabilities, and this is a rare opportunity to lead both the architecture and delivery of a modern AI platform built on Databricks and the Microsoft ecosystem.

This is a hands-on leadership role for someone who has designed and built enterprise AI platforms-not just AI strategy. You’ll define the architecture, lead a growing AI engineering team, and deliver production-grade AI solutions that are secure, governed, and scalable.

This is a builder-first leadership opportunity for someone who enjoys designing enterprise AI platforms, solving complex technical challenges, and creating scalable AI capabilities that deliver measurable business impact.

What You’ll Do Lead the enterprise AI strategy, architecture, and technical roadmap. Design and build production AI/ML platforms using Databricks as the core enterprise AI platform. Architect and deploy production-grade LLM, RAG, Agentic AI, and intelligent automation solutions. Build and scale an AI engineering organization while establishing engineering standards and best practices. Partner with Data Engineering and business leaders to operationalize AI solutions that deliver measurable business value. Drive adoption of AI capabilities including Microsoft Copilot, Power Automate, and intelligent automation. Technical Environment

The successful candidate should have hands-on experience with enterprise AI development using Databricks, including:

Delta Lake / Lakehouse architecture Unity Catalog MLflow (experiment tracking, Model Registry, lifecycle management) Feature engineering Model serving and production monitoring Vector Search RAG architectures Databricks Genie / Mosaic AI (or similar GenAI capabilities) End-to-end AI workflow orchestration Production AI Expectations

Requirements

This is a production enterprise environment. Candidates should have experience designing AI solutions that include:

AI governance and Responsible AI Auditability and lineage RBAC and enterprise security Model lifecycle management Production monitoring and evaluation Governed enterprise data supporting AI workloads Ideal Background 10+ years in AI, Machine Learning, Enterprise Data Platforms, or related engineering disciplines. Experience architecting enterprise AI platforms from the ground up. Strong hands-on Databricks experience. Experience building and leading AI engineering teams. Ability to discuss architecture in depth with senior technical leadership. Strong communication skills with both executive stakeholders and engineering teams.

Benefits & conditions

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.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:27 min

Managing traffic and tracking costs with Databricks Unity Catalog

Viktoria Semaan Viktoria Semaan · World Congress 2026 Europe

3:24 min

The governance failures of centralized data lakes

Mario Meir-Huber · LIVE

3:56 min

Leveraging GitOps for AI auditing and instant rollbacks

Jaroslaw Gajewski Jaroslaw Gajewski · World Congress 2026 Europe

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

2:50 min

Executing LoRA fine-tuning using serverless Databricks AI runtimes

Viktoria Semaan Viktoria Semaan · World Congress 2026 Europe

2:36 min

Managing new AI workloads for non-technical employees

Michael Coté Michael Coté · World Congress 2026 Europe

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