# Fortune 500 — VP of AI Center of Excellence

- Generated: 2026-09-30 08:46:56 PM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4472304190/
- Provider: LinkedIn
- Posted: 11 hours ago at capture time
- Elapsed since posting: about one day from LinkedIn relative timestamp
- Applicants: 72 applicants
- Work model/location: Remote - NY, USA. Verified from canonical LinkedIn JD body: Location: NY, USA (Remote).
- Compensation: Not disclosed
- Travel: Not disclosed
- Positioning track: Executive leader
- Fit outcome: PASS — 90%
- Keyword coverage: 26/34 (76.5%); missing: cloud-native architectures, Azure, GCP, vector storage, C-suite executives, AI engineers, enterprise platforms, CRM platforms

## Direct-match strengths

Direct match for enterprise AI roadmap ownership, AI Center of Excellence governance, GenAI and agentic platform leadership, reusable AI assets, cloud-native AI architecture, MLOps, responsible AI, executive evangelism, and multidisciplinary AI team leadership.

## Hard or material gaps

The actual end employer is not identified beyond Fortune 500. Azure and GCP breadth, Salesforce by name, and enterprise-wide CoE ownership at Fortune-500 scale are less direct than Keith's AWS-heavy enterprise advisory, AI platform, governance, and team-building record.

## Evidence map

Weighted score: 68/72 = 94.4%.
1. Enterprise AI roadmap and CoE governance (weight 3, evidence 3/3) — Defined AI strategy, product vision, technical architecture, commercialization roadmap, and governed production AI delivery at IDW; led AI governance/privacy work at MassMutual.
2. Generative AI, agentic systems, and multi-agent frameworks (weight 3, evidence 3/3) — Built AssistX with LLMs, AI agents, RAG, LangChain, LangGraph, MCP, orchestration, evaluation, vector search, and AWS.
3. Reusable AI platforms and assets (weight 3, evidence 3/3) — Designed AssistX as a reusable modular enterprise AI platform supporting 70+ automations across more than 20 workflows.
4. Cloud-native architecture, vector stores, and MLOps (weight 3, evidence 3/3) — Hands-on AWS, FastAPI, PostgreSQL/PGVector, AI evaluation, observability, model flexibility, CI/CD, Docker, and deployment operations; Google Vertex is source-supported.
5. Responsible AI, data privacy, security, and compliance (weight 3, evidence 3/3) — MassMutual AI governance plus AssistX prompt controls, injection screening, human review, evaluation, observability, security, and governance measures.
6. Executive evangelism, storytelling, and stakeholder management (weight 3, evidence 3/3) — Advised 120+ AWS AI/ML customers, trained 180+ solution architects, delivered 36 invited AWS/industry presentations, and communicated with CEOs, VPs, product leaders, and customers.
7. AI team building and literacy (weight 2, evidence 3/3) — Recruited and technically led 11 AI engineers, mentored engineers in code generation, and created 170+ AWS technical enablement assets.
8. Enterprise consulting and digital transformation (weight 2, evidence 3/3) — AWS enterprise advisory, NorthBay AI practice work, TriMark business transformation, MassMutual governance, and IDW AI transformation evidence.
9. Azure, GCP, Salesforce/CRM, and very large Fortune-500 CoE scale (weight 2, evidence 1/3) — Direct AWS and Google Vertex evidence plus SuiteCRM and broad enterprise advisory; Azure and Salesforce by name are not claimed.

## Full normalized job description

Job Title:
Vice President – AI Center of Excellence (CoE)
Location:
NY, USA (Remote)
Seniority Level:
Executive / Vice President
Employment Type:
Full-time
About the Role
We are seeking an experienced, visionary
Vice President of AI Center of Excellence (CoE)
to lead the strategic design, execution, and scaling of artificial intelligence initiatives across the enterprise.
In this role, you will champion the adoption of next-generation AI—with an emphasis on
Generative AI, Agentic systems, autonomous multi-agent frameworks, and cloud-native architectures
. You will play a pivotal leadership role in optimizing software delivery life cycles (SDLC) and core business operations, scaling reusable AI platform assets, establishing ethical AI governance, and serving as the primary AI evangelist for executive leadership and enterprise clients.
Key Responsibilities
Strategic Vision & CoE Governance:
Define and execute the enterprise-wide AI roadmap aligned with organizational goals; establish operating models, standardizations, and ethical AI governance across global delivery units and diverse industry sectors.
Agentic & Generative AI Leadership:
Spearhead the development, orchestration, and scaling of advanced agentic AI systems, autonomous agents, and generative workflows.
Flagship Platform & SDLC Optimization:
Guide the continuous architectural evolution of internal delivery and SDLC optimization platforms, embedding multi-agent systems to streamline engineering efficiency.
Architecture & Cloud Infrastructure:
Oversee enterprise AI deployment and secure integration across major cloud platforms (AWS, Azure, GCP), vector storage, and modern MLOps pipelines.
Reusable Asset Development:
Partner with automation, digital engineering, and data teams to engineer reusable AI components, toolkits, and data products.
Executive Evangelism & Client Engagement:
Serve as the chief AI subject matter expert; engage with C-suite executives and business leaders to translate complex AI architectures into tangible business value narratives.
Talent Mentorship & AI Literacy:
Build, lead, and mentor a high-performing, multidisciplinary team of AI engineers, data scientists, and solution architects, while elevating AI literacy across the broader organization.
Required Qualifications & Experience
Total Experience:
15+ years of progressive technology experience, including
5+ years in senior AI/ML leadership roles
directing large-scale initiatives.
Proven Track Record:
Demonstrated success in architecting and deploying enterprise-grade AI solutions, with demonstrable experience in
Generative AI and Agentic / Multi-Agent systems
.
Cloud & Infrastructure Expertise:
Deep architectural knowledge of major cloud ecosystems (
AWS, Azure, GCP
), scalable AI infrastructure, vector databases, and enterprise MLOps.
Governance & Ethics:
Solid foundation in AI governance, data privacy, responsible AI practices, and security compliance.
Enterprise Ecosystems:
Familiarity with modern enterprise platforms, data architectures, and enterprise systems (e.g., Salesforce / CRM platforms).
Leadership & Communication:
Exceptional executive presence, storytelling, stakeholder management, and cross-functional leadership skills.
Nice-to-Have / Preferred Qualifications
Experience within technology consulting, professional services, or enterprise digital transformation environments.
Hands-on knowledge of agentic orchestration frameworks (e.g., LangChain, AutoGen, CrewAI) and vector search engines.
Experience presenting at major industry conferences, forums, or publishing thought leadership on applied artificial intelligence.

## Artifact metadata

- Resume: https://bit.ly/4hCA6zg
- Cover letter: https://bit.ly/4hUMo7f
- Validation: PASS — 2-page resume (1060 words), 1-page cover letter (249 words); PDF geometry, bounds, annotations, links, visual pages, and keyword coverage verified.
- Google Drive used: No