AI Engineer focused on building production-ready Generative AI systems, with hands-on experience in RAG pipelines, LLM integration, and backend AI infrastructure.
I work on designing and deploying end-to-end AI systems that go beyond prototypes and operate in real-world environments.
- 🔧 Building RAG-based systems for document understanding and retrieval
- 🤖 Developing agentic AI workflows using LangGraph and LangChain
- 🧠 Integrating knowledge graphs & ontologies to improve reasoning and retrieval
- ⚙️ Deploying scalable AI services using FastAPI, Docker, and modern ML infrastructure
- 📊 Optimizing systems for latency, reliability, and real-world usage
- LLMs (OpenAI, Anthropic, LLaMA, Mistral)
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering & Optimization
- LLMOps (evaluation, orchestration, monitoring)
- FastAPI, REST APIs
- LangChain, LangGraph
- Vector Databases (FAISS, Qdrant, Pinecone)
- Knowledge Graphs (Neo4j, GraphDB)
- Docker, Containerization
- Model Deployment & Monitoring
- Async Processing & Scalable APIs
- Building hybrid RAG systems (vector search + knowledge graphs)
- Designing multi-agent AI systems with real-world use cases
- Improving latency, scalability, and reliability of GenAI pipelines
- Exploring secure and robust LLM applications (prompt injection, guardrails)
TODO
- 💼 LinkedIn: https://www.linkedin.com/in/muhammad-asif-679238199
- 📧 Email: asifmaken533@gmail.com
- 💻 GitHub: https://github.com/fisa712
I focus on building AI systems that:
- Work in production, not just demos
- Are scalable, reliable, and efficient
- Combine LLMs with structured knowledge and backend engineering