Senior self-hosted AI & private LLM deployment talent and rates in Coaches & Consultants
Senior self-hosted AI & private LLM deployment engineers serving coaches & consultants run roughly $160–$225/hr. Stack realities for this combination: Calendly + Stripe + ConvertKit + Kajabi/Teachable — common integrations: Calendly + Acuity + ScheduleOnce, Stripe + PayPal + Square, ConvertKit + Kit + Beehiiv. AI-coach companion grounded on coach IP; session-summary generation
What self-hosted AI & private LLM deployment actually requires in 2026
2026 self-hosted: vLLM or SGLang for serving (best throughput), LiteLLM as OpenAI-compatible proxy, llama.cpp or Ollama for CPU/edge, LoRA adapters for per-customer fine-tuning, Kubernetes + KServe for production orchestration. Llama 3.1, Mistral, Qwen, DeepSeek dominate open-source. Self-hosting engineers need GPU memory math (KV cache, batch sizes, tensor parallelism), CUDA-level debugging, and quantization expertise (Q4/Q8/FP8 trade-offs). This is the most specialized AI niche — the talent pool is <2,000 globally and rates reflect it.