# 5C — Senior Vice President of Artificial Intelligence

- Generated: 2026-09-11 07:44:37 PM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4463919157/
- Provider/job ID: LinkedIn 4463919157
- Posting time: LinkedIn displayed `1 day ago` at fetch time
- Elapsed since posting: Approximately one day
- Applicants: Be among the first 25 applicants
- Work model/location: Remote — United States (role-specific JD text states this is a full-time, remote role)
- Employment type/seniority: Full-time / Executive
- Compensation: Not disclosed
- Travel: Not disclosed
- Positioning track: Executive leader
- Fit outcome: PASS — 85%

## Fit decision

PASS. Keith directly matches the central mandate of setting AI strategy, defining product and infrastructure roadmaps, building AI platforms, leading engineering organizations, translating enterprise requirements, and establishing responsible-AI governance. His production platform, distributed AWS, data-pipeline, enterprise advisory, and executive leadership evidence covers 85% of the weighted requirements with no hard gap. The most important caveat is specialization: Keith's strongest infrastructure record is cloud AI, distributed data, and production platforms rather than physical data-center operations, HPC administration, or low-level GPU optimization.

## Weighted evidence map

| Requirement | Weight | Evidence score | Evidence |
|---|---:|---:|---|
| Set and execute enterprise AI strategy across business divisions | 3 | 3 | Direct strategy, roadmap, architecture, delivery, and operating ownership at Intelligent DataWorks; prior enterprise AI practice leadership. |
| Define AI product and infrastructure roadmaps | 3 | 3 | Direct product/platform roadmaps at Intelligent DataWorks, SuccessKPI, TriMark, and NorthBay. |
| Build scalable AI platforms and distributed cloud architectures | 3 | 3 | Production AssistX architecture, AWS distributed services, data platforms, APIs, orchestration, and enterprise cloud delivery. |
| Lead cross-functional AI research and engineering organizations | 3 | 3 | Built and led AI/engineering teams; led 180+ specialists through AWS technical communities. |
| Model optimization, workload orchestration, and data-pipeline design | 3 | 2 | Direct model routing/cost controls, AI orchestration, evaluation, ML forecasting, Spark/data lakes, and production pipelines; low-level accelerator optimization is less direct. |
| GPU-accelerated training/inference and HPC familiarity | 3 | 1 | Adjacent SageMaker, TensorFlow, Deep Learning AMI, distributed ML, and AI-service architecture experience; no claim of HPC administration or low-level GPU optimization. |
| Translate customer requirements across executive, sales, technical, and operations teams | 2 | 3 | Direct product discovery plus advisory work with 200+ AWS enterprise customers and NorthBay clients. |
| Security, performance, sustainability, and responsible-AI controls | 2 | 2 | Direct security, reliability, privacy, governance, auditability, and model controls; sustainability-specific delivery is not documented. |
| Strategic partnerships and mentoring of senior technical staff | 1 | 3 | Direct strategic-partnership work, team development, executive advisory, and global technical mentoring. |
| Advanced technical degree or equivalent practical experience | 1 | 3 | Ph.D. plus decades of hands-on software, cloud, data, AI, and architecture experience; the JD explicitly accepts equivalent practical experience. |

Weighted result: 61 of 72 possible points = 84.7%, rounded to 85%.

## Direct-match strengths

1. AI strategy and roadmap ownership connected to production delivery.
2. Hands-on cloud, distributed systems, data engineering, workload orchestration, APIs, and platform architecture.
3. Demonstrated AI organization building, mentoring, and cross-functional executive leadership.
4. Enterprise customer advisory at AWS across 200+ organizations.
5. Direct responsible-AI, privacy, security, model-governance, and auditability experience.

## Material gaps and caveats

1. Physical data-center operations and HPC administration are not directly documented.
2. Low-level GPU optimization, quantization, and accelerator-kernel work are not documented; Keith's evidence is at the SageMaker, TensorFlow, cloud-platform, and distributed-architecture layer.
3. Sustainability-specific infrastructure delivery is not documented.
4. Compensation and travel are not disclosed and should be confirmed.
5. The LinkedIn location header says United States; role-specific JD text explicitly verifies remote status.

## Full normalized job description

Company Description
5C is a newly formed AI infrastructure leader created through Hypertec Cloud’s acquisition of 5C Data Centers, combining advanced cloud capabilities with state-of-the-art data centers. The company specializes in large-scale, purpose-built AI digital infrastructure solutions for hyperscalers, high-performance computing providers, AI frontier labs, AI-native companies, and enterprise clients. 5C focuses on delivering AI “factories” designed for the scale, speed, and complexity of emerging industry needs. Its operating principles are built around five pillars: Customization, Celerity, Cutting Edge, Climate, and Cost Efficiency. Team members join a fast-growing environment at the intersection of cloud, data centers, and next-generation AI applications.
Role Description
The Senior Vice President of Artificial Intelligence is a full-time, remote role responsible for setting and executing 5C’s overall AI strategy across Cloud and Data Centers divisions. This leader will define the AI product and infrastructure roadmap, guide the development of scalable AI platforms, and ensure alignment with the needs of hyperscalers, HPC providers, and large enterprise clients. Day-to-day responsibilities include overseeing AI research and engineering teams, evaluating emerging technologies, and driving initiatives in model optimization, AI workload orchestration, and data pipeline design. The SVP will collaborate with executive leadership, sales, and operations to translate customer requirements into differentiated AI solutions while ensuring security, performance, and sustainability standards are met. The role also involves building strategic partnerships, mentoring senior technical staff, and establishing governance frameworks for responsible and compliant AI use.
Qualifications
Strong foundation in Computer Science, with deep understanding of distributed systems, cloud architectures, and scalable AI infrastructure.
Expertise in Data Science and Analytics, including experience with statistical modeling, data engineering, and performance measurement for AI workloads.
Advanced knowledge of Pattern Recognition and Natural Language Processing (NLP), with a track record of applying these techniques to real-world, large-scale applications.
Proven leadership experience in AI, machine learning, or HPC organizations, including building and managing cross-functional technical teams.
Experience defining and executing AI product and technology roadmaps for enterprise or hyperscale environments.
Familiarity with GPU-accelerated computing, model training and inference at scale, and AI-related security and compliance considerations.
Excellent communication and stakeholder management skills, with the ability to collaborate effectively across executive, technical, and customer-facing teams.
Advanced degree in Computer Science, Data Science, Engineering, or related field preferred; equivalent practical experience will be considered.

## Artifact metadata

- Resume: https://bit.ly/4h7RjQZ
- Cover letter: https://bit.ly/4y2pX5G
- Direct resume: https://files.keithsteward.com/5C/Keith_Steward_Senior_Vice_President_Artificial_Intelligence_4463919157_Resume.pdf
- Direct cover letter: https://files.keithsteward.com/5C/Keith_Steward_Senior_Vice_President_Artificial_Intelligence_4463919157_Cover_Letter.pdf
- Archived JD capture: https://files.keithsteward.com/5C/Keith_Steward_Senior_Vice_President_Artificial_Intelligence_4463919157_JD_capture.md
- Validation: 2-page resume (1030 words); 1-page cover letter (250 words); profile 77 words; 40 supported technologies; PDF geometry, annotations, bounds, text extraction, and visual rendering verified.
- Google Drive used: No