Senior self-hosted AI & private LLM deployment talent and rates in Government & Public Sector
Senior self-hosted AI & private LLM deployment engineers serving government & public sector run roughly $160–$225/hr. Stack realities for this combination: Login.gov + Salesforce Gov Cloud + AWS GovCloud + Granicus — common integrations: Login.gov + ID.me identity, Salesforce Government Cloud Plus, AWS GovCloud + Azure Government. Document processing; multilingual chatbots; case-routing
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.