linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving linux docker kubernetes terraform ci/cd python sql prometheus grafana helm argocd aws azure gcp mlflow kubeflow feast airflow ray vllm triton kserve bentoml onnx tensorrt evidently drift registry rag embeddings pgvector qdrant langgraph langfuse evals guardrails mcp agents lora gpu cuda slurm spark kafka dbt iceberg fastapi pydantic pytorch sklearn canary reranking quantization kv-cache batching karpenter tracing gateway retraining fine-tuning delta snowflake databricks bedrock vertex sagemaker litellm ollama tokens context inference serving

The AI Move · UK · UAE · US

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What actually gets you hired

Stop building chatbot demos.

Certificates teach you the theory, not how AI works in production. And every engineer applying for AI roles has already built a basic RAG chatbot or a simple agent that calls one API. AI teams are short of engineers who can put a model into production, measure it, keep it running and explain every decision behind it. That is what every roadmap and project here is built around.

Who made this

I'm Hamid. I left school at 18 with no degree, became a Senior DevOps Engineer at 20 and a Lead at 21, and I'm one of around 33 Kubestronauts in the UK. I now teach engineers how to run AI in production. Everything here comes from what AI teams actually ask for in interviews and job specs.

If you are thinking

It's too late, everyone is doing AI.

Everyone is talking about AI. Very few engineers can show they have run it in production, and that is the gap employers are hiring for.

I'm not a maths or ML person.

Most of these roles are engineering roles. Teams need people who can deploy, scale and monitor models, not invent new ones.

I'm too busy after work.

Every project here is sized for a weekend or two evenings. One project done properly beats ten tutorials started.

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An interview question AI teams ask

How do you monitor an ML model in production?

What they are testing: Whether you watch the model and its data, not just the server. Uptime alone is not an answer.

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