zohaib z.

🚀8+ years building real-world AI & LLM systems for startups and teams I help founders and teams turn AI ideas into real, working products — starting from PoCs and MVPs, and evolving them into robust, production-ready systems as the business scales. I’m an AI Engineer & Architect with 8+ years of hands-on experience, working closely with startups, founders, and product teams to solve real-world problems using modern Generative AI, LLM systems, and cloud-native architectures. Whether you’re experimenting, validating an MVP, or scaling to production, my focus is on clean architecture, future-proof design, and practical trade-offs — so early AI decisions don’t become bottlenecks later. 🤖 Generative AI & Large Language Model Systems I design and implement model-agnostic LLM architectures, so products aren’t locked into a single provider. ⚫GPT-5.2, GPT-4o, GPT-4 Mini (OpenAI / Azure OpenAI) ⚫Anthropic (Claude), Google Gemini ⚫Prompt engineering, tool/function calling, structured outputs ⚫Multi-model routing, evaluation & fallback strategies ⚫ Embedding AI deeply into product workflows (not just chat) 📚 RAG, Knowledge Bases & Knowledge Graphs I build LLM systems that reason over real data, not hallucinations. ⚫End-to-end LLM-RAG architectures (PoC → MVP → scale) ⚫Vector search + semantic search + hybrid retrieval ⚫Recursive & multi-level chunking strategies ⚫Dynamic context assembly & relevance scoring ⚫Knowledge bases & knowledge graphs (Neo4j) ⚫Hierarchical document structures & graph-based retrieval 🤖 AI Agents & Agentic Workflows I specialize in agentic systems that actually perform work, not just respond to prompts. ⚫Single & multi-agent architectures (planner, executor, critic) ⚫LangChain, LangGraph, Cloud Agent SDK, AutoGen, CrewAI ⚫Agent orchestration, agent protocols & A2A patterns ⚫Tool-using agents for operations, analytics & automation ⚫Stateful agents with memory & human-in-the-loop controls ⚫Event-driven and workflow-based agent system ⚙️ MLOps, LLMOps & Observability I treat AI like production software, not experiments. ⚫CI/CD for ML & LLM pipelines ⚫Dockerized & Kubernetes-based deployments ⚫MLflow, Vertex AI, Azure Machine Learning ⚫Model versioning, evaluation & rollback strategies ⚫LLM observability with Langfuse ⚫Metrics & monitoring using Prometheus & Grafana ⚫Cost-aware inference & performance optimization ☁️ Cloud & Infrastructure Architecture I’ve built and deployed AI systems across all major cloud platforms and modern infra stacks. ⚫AWS, Azure, GCP (Cloud Run, production pipelines) ⚫Scalable cloud-native deployments ⚫High-availability & fault-tolerant systems ⚫GPU & inference infrastructure (RunPod) ⚫Developer-friendly deployments (DigitalOcean) ⚫Data Engineering & analytics pipelines (including AWS-native data services) 🧩 Backend & Frontend Engineering I bridge AI + product engineering, so systems ship end-to-end. ⚫FastAPI / Flask backend services ⚫Secure APIs, async systems, auth & permissions ⚫TypeScript, React for frontend applications ⚫Full-stack AI product development ⚫Contract-driven APIs & system integration 🎯 How I Add Value ✔ Help founders experiment fast without painting themselves into a corner ✔ Design PoCs and MVPs that naturally evolve into production systems ✔ Translate business goals into practical AI architectures ✔ Build AI systems for real users, real traffic, real constraints I don’t just “plug in ChatGPT.” I architect AI systems that fit your product, your data, and your stage. 🤝 Let’s Talk If you’d like to brainstorm an idea, validate an approach, or plan your AI roadmap, I’m available for consultations 💬