I specialize in bridging the gap between robust infrastructure and intelligent automation. My work focuses on building Durable AI Agents and scaling mission-critical workloads across multi-cloud environments.
- Orchestration: LangChain, LangGraph, Temporal.io SDK (Durable Execution).
- Models: Fine-tuning Mistral, Hugging Face, OpenAI/Claude API integration.
- Vector Ops: FAISS, ChromaDB, Pinecone, RAG Optimization.
- Agent Patterns: Tool-calling, Multi-agent collaboration, Self-correction loops.
- Infrastructure: Kubernetes (EKS, GKE, AKS), Terraform, AWS CDK, Docker.
- Architecture: High-Availability Data Center design, Disaster Recovery, Hybrid Cloud.
- Managed Services: AWS Lambda, Amazon Aurora, Azure AD, Google Cloud Run.
- Monitoring: OpenTelemetry, Prometheus, Grafana.
- Languages: Python (FastAPI, Django, PyTorch), Go, TypeScript.
- Database: PostgreSQL, Redis, MongoDB, Vector Databases.
Developing resilient AI agents using Temporal.io to manage long-running stateful executions. By combining LangChain with Temporal, I ensure that complex AI reasoning tasks are fault-tolerant and human-in-the-loop ready.
High-Precision Information Extraction & Orchestration
Developed a sophisticated Cloud Agentic Model using PyTorch and Hugging Face (Mistral/Gemini) designed to process large-scale datasets for enterprise deployment. This project optimizes the transition from unstructured career documents to structured data through advanced retrieval and cost-efficient inference.
🛠 Technical Architecture Model Orchestration: Leverages Hugging Face transformers and PyTorch for fine-tuning Mistral-7B, serving as the core reasoning engine.
Cloud Agent Logic: Implemented a cloud-native agent capable of Cloud Reconnaissance (Cloud Reco) to dynamically allocate resources, significantly reducing latency and operational overhead.
Search & Ranking: Employs Hybrid Search (Vector + Keyword) paired with a Cross-Encoder re-ranker to ensure the highest accuracy in document retrieval.
Cost Efficiency: Integrated Gemini and custom quantization techniques to reduce API token consumption and "authoring" costs without sacrificing parsing precision.
Leading the architecture for multi-tenant SaaS platforms, focusing on automated provisioning and scaling ML services for high-traffic applications.
- LinkedIn: linkedin.com/in/joelwembo
- Website: prodxcloud.com
- Email: [[email protected]]
"Building systems that don't just run, but think and endure."