Welcome to the AI Engineering Roadmap! This repository is a comprehensive guide for software engineers, ML engineers, and architects who want to master the art of building, deploying, and scaling AI systems in real-world production environments.
In the world of AI, the model is just a small piece of the puzzle. This roadmap focuses on the Engineering excellence required to make AI reliable, scalable, and cost-effective.
The repository is structured into logical modules, covering the entire lifecycle of an AI product:
Designing resilient and scalable AI infrastructures.*
- Functional vs. Non-functional requirements in AI.
- Latency, Throughput, and Reliability.
- Caching strategies & Message Brokers.
- *Project: Designing a high-traffic AI FAQ system.
Modern blueprints for AI-driven applications.*
- Monolith vs. Microservices for ML.
- Advanced RAG (Retrieval-Augmented Generation) Architectures.
- Agentic Workflows & Tool Use.
- Event-Driven AI Pipelines.
Making AI fast, efficient, and affordable.
- Model Quantization, Pruning, and Distillation.
- GPU vs. CPU Inference trade-offs.
- Batching & Parallelism.
- Memory & Cost Optimization.
Building with confidence.
- Experiment Tracking (MLflow, W&B).
- Prompt Versioning & Management.
- LLM Evaluation Frameworks (RAGAS, etc.).
- Testing & Data Validation.
Shipping AI to the real world.
- Containerization (Docker & Kubernetes).
- Model Serving (vLLM, Triton, FastAPI).
- CI/CD Pipelines for ML.
- Canary & Blue-Green Deployments.
Keeping systems healthy.
- Monitoring Model Drift & Latency.
- Logging & Alerting in AI systems.
- Security & Data Privacy.
A curated list of tools we explore in this roadmap:
- *Frameworks: LangChain, LlamaIndex, Ray.
- Serving: vLLM, BentoML, TGI.
- Data: Pinecone, Qdrant, Weaviate, pgvector.
- Ops: MLflow, Docker, Kubernetes, Prometheus.
As an AI Engineer, my goal is to bridge the gap between "it works on my laptop" and "it works for millions of users." This repo serves as my personal R&D lab and a community resource.
Status: 🚧 Work in Progress. Contributions and Stars are welcome!*
Maintained by: Sepideh Hosseinian Building the future of Engineering in the age of AI.