AI Engineer

Core Infrastructure & Deployment Containerization

Master Docker for packaging models. Orchestration

Use Kubernetes (K8s) for managing clusters. GPU Architecture

Understand NVIDIA CUDA, ROCm, and vGPU allocation. Model Serving

Deploy via vLLM, Ollama, TGI, or Triton Serving Server. Model Management & Optimization Quantization

Apply AWQ, GPTQ, or GGUF to fit models into local VRAM. Fine-Tuning

Execute PEFT and LoRA for local domain adaptation. Open-Source Selection

Evaluate weights from Hugging Face (e.g., Llama, Mistral, Phi). Hardware Benchmarking

Calculate memory bandwidth and compute requirements. Agent Architecture & Integration Framework Mastery

Build workflows using LangChain, LangGraph, or AutoGen. Vector Databases

Deploy and manage local instances of Pinecone, Qdrant, Milvus, or PGVector. RAG Pipelines

Construct robust Retrieval-Augmented Generation systems without cloud APIs. State Management

Handle complex agent memory loops locally. On-Premise Security & Networking Air-Gapped Workflows

Install dependencies and models without internet access. Data Privacy

Implement strict local data governance and access controls. Local Auditing

Set up private logging and guardrails (e.g., NeMo Guardrails). Software Engineering & DevOps Languages

Python and Rust or C++ for speed. Java Microservices. CI/CD Pipelines

Automate local builds with GitLab CI or Jenkins. Monitoring

Track system metrics using OpenTEL, Prometheus and Grafana.