David vonThenen
AI/ML Leader | Keynote Speaker | Book in Progress | Agentic AI, Deep Learning, Production AI | OSS Engineer & Developer Advocate | Python, Go, C++
E-mail: davidvonthenen [ at ] gmail.com / LinkTree: linktr.ee/davidvonthenen
Summary
build production AI systems and the technical narratives that help teams understand, trust, and adopt them.
My work sits at the intersection of AI engineering, applied architecture, technical strategy, and developer education. I’ve spent 20+ years building production software across AI/ML, speech and NLP, cloud-native platforms, Kubernetes, storage, virtualization, and backup/recovery. I’m focusing on shaping AI strategy, building proof-of-concepts for emerging products, and designing explainable AI systems with the governance needed for enterprise deployment.
I focus on Agentic AI, Retrieval-Augmented Generation, Graph RAG, Document RAG, multi-agent systems, AI memory, and the infrastructure patterns that make those systems reliable in the real world. That includes retrieval architectures that explain where answers came from, governance workflows that track data and model provenance, and systems that treat observability, lineage, and reproducibility as first-class requirements rather than decorative compliance confetti.
My background is both deeply technical and market-facing. I’ve built and trained models, designed AI architectures, contributed to open-source platforms, led engineering teams, launched SDKs, supported customer architecture reviews, created demos, built workshops, and partnered with product, sales, and marketing teams to turn complex technology into adoption. At Deepgram, I helped grow Python SDK usage from 10M to 118M calls and launched a Go SDK that generated 5M+ calls in its first month. At Symbl.ai, I founded the Go SDK and related integrations that helped support the company’s first $60K edge-platform contract. Earlier, I managed a 20+ engineer team whose virtualization work helped grow a business unit from $880M to $2.18B. I also teach what I learn. I have spoken at NVIDIA GTC, Devoxx, ODSC, DeveloperWeek, SCaLE, and WeAreDevelopers on explainable AI, adaptive RAG, agentic systems, model quantization, multimodal ML, voice cloning, and small language model training.
What motivates me is building AI that can survive contact with production: systems that are observable, measurable, explainable, and aligned with real customer needs. I’m interested in roles that combine AI engineering leadership, technical strategy, product architecture, technical marketing, thought leadership, analyst relations, and developer education.
Work Experience
NetApp (April 2025 – Present) – Senior AI/ML Engineer, Office of the CTO
At NetApp, I have focused on turning emerging AI concepts into practical enterprise architectures, working across executive strategy, technical consulting, and hands-on prototyping. My work centers on designing governed RAG and agentic AI systems that connect storage, data lineage, retrieval, and model behavior into architectures enterprises can actually operate. Through customer-facing guidance, internal strategy work, open-source prototypes, and conference talks, I help translate complex AI patterns into clear engineering direction for scalable, auditable, and production-ready systems.
* Shape AI/ML strategy by identifying market opportunities, leading technical strategy sessions with executive leadership, and building proof-of-concepts for emerging products and new market entry points.
* Designed and delivered an open-source RAG architecture integrating NetApp ONTAP, FlexCache, and SnapMirror to support scalable short- and long-term AI memory, explainable knowledge-graph grounding, governance, and enterprise upgrade paths.
* Built an AI governance framework centered on data lineage and provenance, treating datasets like code with immutable commits, versioned pipelines, and policy-as-code gates for reproducibility, auditability, and compliance.
* Presented AI sessions and workshops numerous AI conferences (such as Devoxx UK, ODSC East, and WeAreDevelopers), translating advanced RAG, agentic AI, and adversarial techniques into practical engineering patterns.
For a comprehensive list of presentations and workshops, visit https://davidvonthenen.com/talks.
DigitalOcean (Nov 2024 – Apr 2025) – Senior AI/ML Developer Advocate II
At DigitalOcean, I translated complex AI/ML capabilities into practical developer-facing stories that connected technical depth with cloud platform adoption. I built customer-focused proof-of-concepts, created hands-on content and workshops across explainable AI, RAG, voice cloning, multimodal classification, and deployment patterns, and used those assets to show developers how AI workloads could run effectively on DigitalOcean. Through major conference talks and workshops at NVIDIA GTC, DeveloperWeek, Devoxx France, All Things Open AI, and SCaLE 22x, I helped position DigitalOcean as a credible platform for applied AI by turning emerging machine learning concepts into demos, narratives, and technical education that developers could immediately understand and use.
* Built and trained AI/ML models for customer proof-of-concept projects while supporting strategic initiatives to increase cloud platform adoption and AI/ML-related revenue.
* Created practical technical content and workshops covering explainable AI with Captum, knowledge-graph RAG, voice cloning, multimodal classification, and cloud deployment patterns.
* Delivered talks and workshops at NVIDIA GTC, DeveloperWeek, Devoxx France, All Things Open AI, and SCaLE 22x, including keynote-level sessions on voice cloning and real-time medical-condition classification.
For a comprehensive list of presentations and workshops, visit https://davidvonthenen.com/talks.
Deepgram (Oct 2023 – Nov 2024) – Staff Engineer / Customer Succeess
At Deepgram, I bridged deep engineering work with developer advocacy, helping turn speech AI from a platform capability into practical customer solutions. My work spanned SDK modernization, conversational AI architecture, RAG-enabled voice applications, and deployment guidance across cloud, hybrid, and on-prem environments. I also worked closely with sales, product, and marketing to translate technical capabilities into demos, architecture reviews, and adoption-focused content that helped customers understand how to build reliable, low-latency AI systems with Deepgram’s platform.
* Refactored the Python SDK and .NET SDK, then introduced the Go SDK; grew Python SDK usage 10x from 10M to 118M calls and drove 5M+ calls on the Go SDK in its first month.
* Built customer-facing conversational AI solutions combining speech recognition, retrieval-augmented generation, custom NLP models, and production deployment patterns.
* Designed scalable AI infrastructure guidance for on-premises, cloud, and hybrid deployments, balancing cost, latency, reliability, and customer integration constraints.
* Partnered with sales, product, and marketing teams on technical content, demos, customer architecture reviews, and campaign support to increase platform adoption.
Symbl.ai (Aug 2022 – Aug 2023) – Head of DevRel / Principal Developer Advocate
At Symbl.ai, I helped move developer relations from a support function into a revenue-facing technical engine. I built the foundation for the company’s developer advocacy program across SDKs, enablement, integrations, technical content, sales support, and customer-facing demos, while also creating key product extensions such as the Go SDK, LangChain integration, WebRTC workflows, and AI-agent prototypes. The work sat at the intersection of architecture, customer consulting, and market education, helping developers and buyers understand how conversation intelligence could become part of real generative AI applications.
* Supported customer confidence and market momentum through technical enablement leading into the Invoca acquisition.
* Established the developer advocacy program, including training materials, SDK maintenance, developer content, customer integrations, sales support, and social/technical marketing workflows.
* Founded the Symbl.ai Go SDK, directly securing the inaugural $60K contract and supporting subsequent customer revenue opportunities.
* Created Symbl.ai’s first LangChain integration, enabling customers to build generative AI workflows for conversation intelligence; also built WebRTC and AI-agent integrations.
VMware (Oct 2010 – Aug 2022)
Modern Applications Platform Business Unit (Feb 2018 to Aug 2022) – Staff Software Engineer
Cloud Native Engineer and Developer Advocate, who provided the initial foundation for VMware’s Kubernetes strategy. Architected and implemented multiple critical Kubernetes services that enabled VMware to operate as a Kubernetes cloud provider. This required writing an enormous amount of software development and evangelizing initiatives in the Kubernetes ecosystem.
*Served as a founding contributor to VMware’s Kubernetes strategy, helping establish VMware as a Kubernetes cloud provider across infrastructure, storage, and developer ecosystems.
* Architected and contributed to Tanzu Community Edition, vSphere CSI Driver, and Cloud Provider vSphere, enabling Kubernetes persistent storage, cluster integration, and vSphere-native operations.
* Contributed to Kubernetes SIGs, open-source community initiatives, technical content, and developer education to accelerate cloud-native adoption.
Dell/EMC – Emerging Technologies Division (Oct 2015 – Feb 2018) – Staff Software Engineer
Transferred into Dell/EMC’s Emerging Technology Division where I took on Developer Advocate role with the Dell/EMC {code} team. I was tasked to create open source projects and contributions to the Kubernetes and Docker ecosystems that aligned with Dell/EMC’s software initiative. The {code} team and projects were transferred to VMware (above) to increase acceleration/adoption.
* Created open-source projects and technical integrations aligned with Dell/EMC software strategy across Kubernetes, Docker, storage, and developer tooling ecosystems.
* Built developer-facing demos, technical content, and community programs that later transferred into VMware to accelerate Kubernetes and cloud-native platform adoption.
Dell/EMC – Backup/Recovery Solutions (Oct 2010 – Oct 2010) – Sr. Principal Software Engineer
Lead Software Engineer turned team manager for 20+ on Backup/Recovery solutions specializing in VMware Virtualization backup. Grew the business unit’s revenue from $880 Million to $2.18 Billion, and 80% of that revenue increase was directly attributed to our development of virtualization backup.
* Managed a 20+ engineer team building backup/recovery systems for VMware virtualization environments, spanning architecture, implementation, team execution, and product delivery.
* Helped grow the business unit from $880M to $2.18B, with ~80% of the revenue increase attributed to virtualization backup capabilities developed by the team.
* Designed and implemented core backup/recovery capabilities later reflected in issued patents covering incremental VM backup, application-aware policy dependency detection, linked clone inheritance, VM restore, and administrator validation.
QLogic Corporation (Jan 2006 – Oct 2010) Staff Software Engineer
*Developed and optimized remote management applications and drivers for Fibre Channel (FC), Fibre Channel over Ethernet, and iSCSI storage adapters, including ASIC firmware programming for manufacturing. Every 4GB and 8GB storage adapter shipped was programmed and managed by software I had built.
Unisys Corporation (Sept 2003 – Jan 2006) Software Engineer 4
Intel Corporation (April 2003 – Sept 2003, 6 Month Contract) BIOS Validation Engineer
Conexant Systems/Mindspeed Technologies (Feb 2001 – June 2002) Software Engineer
Bachelor of Science in Computer Science, University of California, Irvine
Specialization(s): Networks/Distributed Systems, Embedded Systems
Bachelor of Science in Chemistry, University of California, Irvine
Specialization(s): Organic Chemistry
AI/ML: LLMs, RAG (Vector, Graph, BM25, Hybrid), adaptive RAG, agentic AI, agent memory (mem0 and menu), multimodal ML, NLP, ASR (Speech-to-Text), Text-to-Speech, conversational AI, metadata data mining, explainable AI, HIPAA/GDPR governance, reinforcement learning, fine-tuning, quantization, LLM creation and optimization
Frameworks and Models: PyTorch, Hugging Face Transformers, scikit-learn, Pandas, NumPy, CUDA, OpenAI, Anthropic Claude, Google Gemini, LangGraph, CrewAI, Meta Llama/Llama.cpp, Mistral, Falcon
Retrieval, Data, and Governance: OpenSearch, Neo4j, Cypher, vector embeddings, semantic search, Elasticsearch, FAISS, Pinecone, Redis, SQL, NoSQL, data lineage, provenance, policy-as-code
Cloud, Platform, and Infrastructure: Kubernetes, Docker, Linux containers, AWS, Azure, Google Cloud, DigitalOcean, VMware vSphere, Nebius, Lambda Labs
Languages and Leadership: Python, Go, C/C++, Java, Rust, JavaScript; SDK ownership, open-source strategy, developer advocacy, executive technical strategy, workshops, keynote speaking
US9292327B1 – Optimization for incremental backup of VMs
US9389964B1 – Read-write access in a read-only environment
US9026500B1 – Restoring virtual machine data
US9355235B1 – Validating a user of a virtual machine for administrator/root access
US10467034B1 – Performing application specific actions without in-guest credential information