# Enzo Tech Group — Director of Artificial Intelligence

- Generated: 2026-09-13 05:26:53 PM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4464317017/
- Provider: LinkedIn
- Posted: approximately 2026-09-07 05:26 PM EDT (from '6 days ago')
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp
- Applicants: Over 200 applicants
- Work model/location: Remote — United States; occasional travel, percentage not disclosed
- Compensation: Up to $300,000 annual base salary
- Travel: Occasional; percentage not disclosed, so confirm it remains within 5%
- Positioning track: Executive leader
- Fit outcome: PASS — 88%

## Direct-match strengths

Enterprise AI strategy, production GenAI/LLM platforms, MLOps, AWS, data ecosystems, AI governance, security, responsible AI, organization leadership, executive advising, cloud modernization, reusable frameworks, and measurable business outcomes.

## Hard or material gaps

The end employer is unnamed. Direct line-management scope is documented through 25 people, while the JD seeks a large multidisciplinary organization without giving a number; Keith's 180+ AWS specialist communities add influence-at-scale evidence but are not represented as direct reports. Manufacturing experience is preferred, not required.

## Evidence map

1. Define enterprise AI engineering strategy (weight 3, evidence 3/3) — Direct AI strategy, roadmaps, investment priorities, and delivery leadership.
2. Build enterprise-scale AI/ML platforms (weight 3, evidence 3/3) — Direct production AI, cloud, data, and reusable platform delivery.
3. Generative AI, LLMs, and intelligent automation (weight 3, evidence 3/3) — Direct AssistX LLM, RAG, agents, and 70+ automations.
4. MLOps, model lifecycle, and AI infrastructure (weight 3, evidence 2/3) — Direct evaluation, releases, monitoring, governance, and operations; infrastructure breadth is AWS-led.
5. Lead a large multidisciplinary engineering organization (weight 3, evidence 2/3) — Direct organizations up to 25 and global technical communities totaling 180+; not claimed as 180 direct reports.
6. Governance, security, compliance, and responsible AI (weight 2, evidence 3/3) — Direct financial-services governance, privacy, IAM, auditability, and responsible-AI evidence.
7. Enterprise modernization through AI (weight 2, evidence 3/3) — Direct legacy-to-cloud, data-lake, SaaS, and AI transformation outcomes.
8. Industrial or manufacturing background (weight 1, evidence 1/3) — Transferable enterprise operations and supply-chain data work; manufacturing specialization is not claimed.
9. Executive communication and influence (weight 2, evidence 3/3) — Advised 200+ enterprise customers and multiple C-suite leadership teams.

## Keyword diagnostic

Direct alignment with enterprise AI strategy, production platforms, GenAI, governance, modernization, executive influence, and technical-organization leadership; team-scale claims remain source-accurate.

## Full normalized job description

Director of AI Engineering
My client, a leading US Fortune 500 industrial manufacturing company, is seeking a
Director of AI Engineering
to lead the strategy, development and delivery of enterprise AI platforms and intelligent solutions across a global organisation.
This is a highly visible leadership role responsible for defining the AI engineering vision, scaling production-grade AI capabilities and driving the adoption of Generative AI, machine learning and intelligent automation across the business.
You will work at the intersection of AI innovation, cloud engineering and executive leadership, shaping how artificial intelligence is built, governed and deployed to deliver measurable business value.
What You'll Do
Define and lead the enterprise AI engineering strategy in alignment with business and technology objectives
Oversee the design, development and deployment of scalable AI and machine learning platforms across the organisation
Drive the adoption of Generative AI, LLMs and AI-powered applications to improve operational efficiency and customer outcomes
Build robust AI infrastructure, MLOps pipelines and reusable engineering frameworks to accelerate AI delivery
Partner with Product, Digital, Data, Architecture and business leaders to identify and deliver high-impact AI use cases
Establish engineering standards across AI governance, model lifecycle management, observability, security and responsible AI
Influence strategic roadmaps across AI platforms, cloud infrastructure, data ecosystems and enterprise applications
Lead, mentor and develop a high-performing organisation of AI engineers, machine learning engineers and technical leaders
Establish governance frameworks covering AI security, compliance, model monitoring and ethical AI practices
Improve the scalability, reliability and performance of enterprise AI platforms while optimising operational costs
Translate complex AI strategies into clear executive recommendations, investment priorities and business outcomes
Drive measurable business value through the successful delivery of enterprise AI initiatives at scale
What We're Looking For
Senior leadership experience within AI Engineering, Machine Learning Engineering or Enterprise AI Platforms
Proven experience building and leading large, multidisciplinary engineering teams
Deep expertise in cloud-native AI platforms, with strong experience across Azure, AWS or Google Cloud
Experience designing and deploying enterprise-scale AI and machine learning solutions into production
Strong understanding of MLOps, AI infrastructure, model lifecycle management and AI platform engineering
Experience working with Large Language Models (LLMs), Generative AI and modern AI frameworks
Background within manufacturing, industrial, engineering or another large-scale enterprise environment is highly desirable
Strong understanding of AI governance, security, compliance and responsible AI principles
Demonstrated success modernising enterprise technology through AI-driven transformation
Ability to operate effectively at both executive and technical levels
Exceptional communication skills with the ability to influence senior stakeholders across the organisation
Technologies and Areas You'll Work With
Generative AI • Large Language Models (LLMs) • Machine Learning • AI Engineering • MLOps • Azure AI • Azure OpenAI • Azure Machine Learning • Python • Kubernetes • APIs • Vector Databases • AI Agents • Cloud Platforms • Responsible AI • AI Governance • Model Monitoring • Enterprise AI Platforms • Intelligent Automation
Details
Industry:
Industrial Manufacturing
Location:
Remote (Occasional Travel)
Compensation:
Up to $300,000 per year base salary
Job Type:
Full Time
Why This Role
This is a career-defining opportunity to lead enterprise AI engineering strategy and shape the future of AI across one of the world's largest industrial organisations.
You will have the opportunity to build the engineering foundations that power next-generation AI capabilities, intelligent automation and digital transformation initiatives while working alongside executive leadership to deliver meaningful business outcomes at global scale.

## Artifact metadata

- Resume: https://bit.ly/4yBARPW
- Cover letter: https://bit.ly/3VtCNeQ
- Validation: PASS — 2-page resume (915 words), 1-page cover letter (228 words); PDF geometry, bounds, annotations, links, and visual pages verified.
- Google Drive used: No