Candidate Profile — Candidate #6
Position: Modular — Engineering Director, GenAI Enterprise (Remote)
Candidate Location: San Francisco Bay Area
Experience: 32.0 years experience
Relevant Experience & Education Highlights
Brings 32 years of technical leadership in customer-facing AI platforms, cloud-native infrastructure, and GenAI solutions, strongly aligning with directing Modular's GenAI Enterprise team.
1. Serve as the primary engineering point of contact for enterprise prospects and customers
Drove customer success through deep technical engagement on complex infrastructure and AI challenges.
- Led design and rollout of nationwide CI/CD automation framework for a major wireless provider's Open RAN 5G network across thousands of cell sites.
- Delivered GenAI platform automation with NVIDIA integration for Cloud Service Providers to enable multi-tenant AIaaS monetization.
- Architected cloud-native 5G RAN infrastructure using VMware TCA, TKG, and VMC for hybrid cloud operations.
- Cultivated relationships with technical stakeholders in deploying production AI workloads and edge computing solutions.
2. 3+ years of management experience with a proven track record of building high-performing collaborative teams
Provided executive technical leadership across multiple high-stakes engineering initiatives.
- Served as Chief Architect and Founding Engineer directing machine intelligence platform development prioritizing determinism and transparency.
- Directed R&D for AI-powered mobile infrastructure and next-generation 5G platforms at a telecommunications research firm.
- Led as Director of Research and Development for cloud networking, SDN, NFV, and data center solutions.
- Guided architectural vision and technical roadmaps as Principal Architect in data center management software.
3. Hands-on experience with production AI workloads including scaling and serving large models
Demonstrated expertise in GenAI execution lifecycle, deployment, and optimization for enterprise-scale systems.
- Enabled GPU as a Service layers for production-ready Generative AI platforms supporting CSP monetization.
- Advanced SONiCS platform integrating AutoML, NAS, and AI features for low-latency RAN and MEC.
- Developed proficiency in Python, C++, CUDA, and PyTorch for AI infrastructure and large model handling.
- Automated full lifecycle CI/CD pipelines with Airflow, GitLab, Kubernetes, and Terraform for disaggregated workloads.
Requirements & Candidate Alignment
| Modular Requirement | Candidate Qualification |
|---|---|
| 7+ Years of experience in a customer-facing technical roles where you solved hard problems alongside clients | 32 years of technical leadership delivering customer-specific infrastructure and AI solutions |
| 3+ Years of management experience with a proven track record of building high-performing collaborative teams | Extensive management across Chief Architect, Founding Engineer, and Director roles building R&D teams |
| In-depth understanding of the GenAI execution lifecycle, deployment methodologies, along with testing and quality evaluation methodologies | Deep GenAI expertise from automating platforms like VMware Private AI Foundation with NVIDIA |
| Proven ability to translate complex technical concepts into clear, concise, and understandable language that resonates with for both clients and internal teams | Strong communication demonstrated in leading nationwide deployments and stakeholder engagements |
| Demonstrated ability to rapidly prototype and deliver Proofs of Concept (POCs) that win customer confidence | Proven POC delivery through zero-touch provisioning and live upgrades at scale for telco networks |
| Adept at navigating ambiguity and ability to exercise sound judgment to identify appropriate solutions and tools, while avoiding unnecessary complexity | Expertise in ambiguity via founding roles architecting cloud-native 5G and AI platforms |
| Hands-on experience with production AI workloads including scaling and serving large models | Production AI scaling in GenAIaaS, GPU services, and edge AI infrastructure |
| Proficiency in Mojo, Python, C++, or CUDA programming languages, plus familiarity with frameworks such as MAX, Pytorch, or vLLM | Proficient in Python, C++, and PyTorch for AI workloads and optimization |
If you would like to discuss this candidate or other critical roles, here is a link to my calendar to schedule a call:
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