Jnachi Certified LLMOps & Model Governance Specialist
Validates production infrastructure and operational governance for enterprise large language models. Assesses continuous evaluation pipelines, high-throughput serving architectures (vLLM, TensorRT-LLM, KV Cache optimization), distributed tracing with OpenTelemetry/Langfuse, prompt CI/CD versioning, red-teaming, and compliance with the EU AI Act and NIST AI RMF.
Jnachi Certified LLMOps & Model Governance Specialist
Validates operational and infrastructural mastery in deploying, monitoring, fine-tuning, and governing enterprise large language models at scale.
Exam Competency Matrix & Domain Breakdown
Select any domain below to inspect tested skills, real-world scenarios, and preparation materials.
High-Throughput LLM Serving, vLLM & KV Caching
Inference engines, PagedAttention memory management, KV Cache optimization, continuous batching, and speculative decoding.
PagedAttention algorithm, KV Cache memory fragmentation reduction, continuous batching, and tensor parallelism across multiple GPUs.
Deploying AWQ, GPTQ, and FP8 quantized weights for reduced VRAM footprint and draft-target speculative decoding acceleration.
Portal Registration Required Before Exam
Your full name, location, and organization are verified and printed directly on your official diploma.
Exam Objectives & Tested Competencies
High-Throughput Serving (vLLM, PagedAttention, KV Caching)
Evaluated in scenario-based proctored questions.
Distributed Tracing, Langfuse, OpenTelemetry & Observability
Evaluated in scenario-based proctored questions.
Prompt CI/CD Regression Testing & Fine-Tuning LoRA/QLoRA
Evaluated in scenario-based proctored questions.
EU AI Act, NIST AI RMF, Red-Teaming & Enterprise Guardrails
Evaluated in scenario-based proctored questions.
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