Certified LLMOps Engineer (CLOE)
A globally recognized certification that equips engineers to design, deploy, and operate reliable, secure, and scalable large language model systems across enterprise and cloud environments.
About This Certification
ADaSci Certified LLMOps Engineer (CLE) program is a 30-hour, self-paced certification designed to equip professionals with the skills to build, deploy, and operate reliable, secure, and scalable large language model systems across cloud and enterprise environments.
Covering the full LLM lifecycle, from prompt engineering, fine-tuning, and RAG pipelines to CI/CD automation, cloud and on-premise deployment, observability, and governance, the curriculum blends strong operational foundations with hands-on labs and real-world case studies. This globally recognised certification validates your ability to ensure LLM reliability, performance, security, and compliance at scale, making you a critical enabler of enterprise AI adoption. Ideal for LLMOps, MLOps, DevOps, cloud engineers, and AI platform teams, it accelerates careers at the intersection of AI engineering, infrastructure, and responsible AI operations.
With lifetime validity, structured learning pathways, and recognition by the world’s premier AI body, this certification positions you as a trusted leader in operationalising large language models for real-world, mission-critical applications.
What you'll learn
Program courses
Who this is for
Why get certified.
Recognition
This certification provides industry-aligned, globally relevant recognition validating expertise in designing, deploying, and operating large language model systems at enterprise scale. It demonstrates proficiency across the full LLM lifecycle, including CI/CD automation, cloud and on-premise deployment, observability, security, and responsible AI governance.
Certification holders are recognized for their ability to ensure reliability, performance, compliance, and cost efficiency of AI systems in production environments, strengthening professional credibility for roles in AI platform engineering, MLOps/LLMOps leadership, enterprise AI operations, and large-scale digital transformation programs.
- 30h of content
- 60 exam questions
- Lifetime access
- Verifiable credential
Frequently asked questions.
Continue your LLMOps journey.
Pair your LLMOps Certification with hands-on MLOps and LLM observability courses, adjacent AI engineering certifications, and an ADaSci AI professional membership that keeps your credential active and recognised.
LLMOps and MLOps courses
Mastering LLM Observability with Arize Phoenix
Trace, evaluate and debug LLM applications in production — the observability backbone of LLMOps.
Production-Grade MLOps Primer
Pipelines, registries and deployment patterns that LLMOps engineers reuse for model delivery.
Mastering MLOps Strategies
Operating-model strategies for scaling ML and LLM systems across teams and environments.
Debugging Non-Deterministic Agentic Systems
Diagnose flaky, non-deterministic LLM and agentic behaviour — an essential LLMOps troubleshooting skill.
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