Senior Technical Program Manager | AI Platform & Infrastructure | Distributed Systems Execution
13+ years leading cross-team execution across platform engineering, AI/ML infrastructure, and enterprise systems. I drive complex, multi-team technical programs from ambiguity to shipped, measurable outcomes. Deep technical fluency across distributed systems, AI inference pipelines, cloud infrastructure, and compliance automation.
Currently building production AI systems at Memoriant Inc.: fine-tuned compliance LLMs, GPU-accelerated inference infrastructure, and agentic evaluation frameworks deployed on NVIDIA DGX Spark.
Production AI systems: model training pipelines, inference serving, evaluation harnesses, and observability.
| Project | What It Does | Stack |
|---|---|---|
| cmmc-compliance-ai-model | 10 fine-tuned LLMs (7B-72B) for regulated industries. Latest: OLMo-2 7B v4 (85% eval accuracy, 23h training on DGX Spark). QLoRA/DoRA, GGUF, air-gapped Ollama. Published on HuggingFace. | PyTorch, Unsloth, CUDA, Ollama |
| cmmc-compliance-dataset | 18,202 curated compliance examples across 11 regulatory frameworks. Rebuilt from 67K raw examples (73% noise removed). Gated access with lead capture. | NIST, CMMC, HIPAA, FedRAMP |
| dgx-spark-kv-cache-benchmark | Novel benchmarks on NVIDIA DGX Spark GB10. Discovered 92.5% KV cache collapse at 64K context and unified memory paradox. Published to r/LocalLLaMA, HN, NVIDIA Forums. | llama.cpp, CUDA 13.0, aarch64 |
| governed-llm-gateway | Policy-as-code LLM gateway: tamper-evident audit trails, rate limiting, cost telemetry. 103 tests. | Python, FastAPI |
| el-barto-serve | OpenAI-compatible inference server. Auto-patches Flash Attention for Blackwell GPUs. | Python, PyTorch |
| memoriant-ops-bot | Multi-provider AI agent orchestration via Telegram/Matrix. Manages Claude Code, Codex CLI, Gemini CLI. | Python, WebSocket |
Training the best language model in 16MB on 8xH100s. Only entrant to implement all 7 of OpenAI's explicitly requested research directions. 13 PRs submitted, 8 complete training scripts (11,810 lines of novel research code), 25+ GPU experiments across RTX 5090 and H200 SXM pods.
Record Submissions (3-seed verified):
| PR | Architecture | BPB |
|---|---|---|
| #968 | Order-20 Dirichlet Posterior + Per-Order OBCL + Phrase Cache | 0.1154 |
| #948 | Two-Level Dirichlet Posterior + Phrase Cache | 0.1156 |
| #1127 | 11L XSA-all + EMA + LoRA TTT + Partial RoPE + dim480 | 1.1311 |
Neural Track (progressive improvement):
| PR | Architecture | BPB | Seeds |
|---|---|---|---|
| #406 | 11L XSA4 + EMA + Self-Distillation TTT | 1.1287 | 3 |
| #385 | 11L Int6 QAT + SmearGate + SWA(0.4) + WD=0.04 | 1.1488 | 3 |
| #273 | 10L Int6 QAT + SmearGate + SWA | 1.1575 | 1 |
Research Submissions (all 7 OpenAI-requested architectures):
| PR | Architecture | BPB |
|---|---|---|
| #1192 | Fused Triton Megakernels (RMSNorm + LeakyReLU) | 1.356 |
| #1191 | H-Net Dynamic Chunking (learned tokenization) | 1.359 |
| #1193 | Universal Transformer + Adaptive Density | 1.439 |
| #1195 | Learning Adapters on Random Linear Maps | 2.202 |
| #1196 | LLM-JEPA (Joint Embedding Prediction) | 2.202 |
| #1197 | Mamba-Inspired SSM Hybrid (3:1 SSM:Attention) | 3.317 |
| #1194 | Text Diffusion (MDLM, masked discrete diffusion) | 3.380 |
Novel techniques developed beyond OpenAI's requests: Adaptive Density Training (sparse-to-dense progressive unmasking), Echo Training (self-distillation from EMA checkpoints), Gradient Quilting (per-iteration adaptive LR with auto-freezing).
Infrastructure built: 345,000-vector expert knowledge base (Brain Trust) from 34 AI/ML experts. Competitive intelligence pipeline analyzing 1,084 competitor PRs. Multi-pod experiment orchestration. Full Hessian GPTQ validation on Hopper (H200 SXM).
Deterministic, auditable agent components: evaluation, recovery, orchestration, and compliance enforcement.
| Project | What It Does | Link |
|---|---|---|
| Evaluation Sandbox | Doer/Judge/Adversary/Observer holdout scenario evaluation | Repo |
| Blind Scenario Testing | Black-box behavioral testing of live API systems, 151 tests | Repo |
| Self-Healing Workflows | Retry logic, fallback chains, circuit breakers for agent tasks | Repo |
| Temporal Executive Agent | Dependency-ordered planning and execution with state tracking | Repo |
| MCP Data Agent | MCP server exposing CRM/ticket/database tools to LLMs | Repo |
| Fairness Governor | Weighted round-robin allocation with skew-ratio detection | Repo |
Full suite: agentic-ai-portfolio
Tools for scaling governance across distributed engineering teams in regulated environments (CMMC 2.0, NIST 800-171, HIPAA, FedRAMP, DFARS).
| Project | What It Does | Link |
|---|---|---|
| garak Compliance Probes | LLM vulnerability probes for NVIDIA garak. Fabricated regulatory citations (PR #1658), homoglyph obfuscation (PR #1660), architecture Discussion #1659. Decomposed from monolithic PR #1619 per maintainer architectural feedback. | Repo |
| Governance Graph Compiler | Compiles policy Markdown into DAGs for deterministic audit evaluation | Repo |
| Compliance Validation Agent | Validates workflows against compliance rules, generates audit trails | Repo |
| Patent Platform | Full patent pipeline: search, analyze, draft, review, file. 706+ tests. | Repo |
| Component | Details |
|---|---|
| GPU Infrastructure | NVIDIA DGX Spark (GB10, 128GB) for inference/training. 10G backbone, NFS-mounted NAS (3.6TB models). |
| Distributed Training | 8xH100 SXM on RunPod. torchrun DDP, torch.compile, FA3, GPTQ, zstd/Brotli compression. |
| CI/CD & Automation | GitHub Actions, launchd scheduling, automated replay archival, cron-based scraping pipelines. |
| Observability | Brain Trust dashboard (FastAPI + Qdrant + SSE). GPU benchmarking scripts. Pod performance validation. |
| Containerization | Docker Compose for multi-service deployments. TensorRT-LLM containers for NVFP4 quantization. |
14 published plugins for AI-powered development workflows: patent drafting, architecture review, load testing, documentation drift detection, governance compilation, test coverage analysis, and more.
| Domain | Proof Points |
|---|---|
| Platform Scale | $20M+ portfolios, 700K-user identity systems, multi-cloud (Sales/Service/Data/Marketing Cloud) |
| Cross-Team Execution | Consecutive 5/5 CSAT across multiple client organizations, cycle times cut 67% (6 weeks to 2 weeks) |
| Security & Identity | 200 application SSO (Okta/SAML/OIDC) across federated business divisions |
| Data Platforms | 89M records, 28+ source systems, 99% identity unification, 95.48% match rates |
| Compliance | SOC2/SOX/CMMC/HIPAA/FedRAMP governance structures across independent engineering teams |
| Regulated Environments | Air-gapped AI deployment, CUI-handling systems, DFARS compliance |
MIT Applied Data Science Certificate | Salesforce: Data Cloud Consultant, Administrator, AI Associate | Scrum: CSM | NVIDIA Inception Member
📧 nmaine@gmail.com | LinkedIn | nathanmaine.com | HuggingFace | Memoriant Inc.