Building production-grade AI systems and scalable infrastructure
AI/ML Engineer with expertise in building production-scale multi-agent systems, distributed architectures, and full-stack applications. Specialized in Large Language Models, RAG orchestration, and cloud-native infrastructure. Active technical content creator at Cyber Creed with a focus on AI systems, software architecture, and cybersecurity.
Current Focus: Advanced LLM orchestration patterns, agentic AI systems, and distributed computing at scale.
Languages: Python, R
Frameworks: TensorFlow, PyTorch, JAX
LLM Stack: LangChain, LlamaIndex, Hugging Face
OpenAI API, Anthropic Claude
Vector DBs: Pinecone, Weaviate, ChromaDB, Qdrant
MLOps: MLflow, Weights & Biases, DVC
Data: Pandas, NumPy, Polars, Dask
Visualization: Matplotlib, Plotly, Seaborn |
Languages: Python, JavaScript/TypeScript, Go
Frameworks: FastAPI, Flask, Node.js, Express
Databases: PostgreSQL, MongoDB, Redis
Cassandra, DynamoDB
Message Queue: Apache Kafka, RabbitMQ, Redis Streams
Cloud: AWS, Azure, GCP
Containers: Docker, Kubernetes, Helm
IaC: Terraform, Pulumi, CloudFormation
CI/CD: GitHub Actions, GitLab CI, Jenkins |
- Microservices Architecture | Event-Driven Systems | CQRS & Event Sourcing
- Multi-Agent Systems | RAG Orchestration | Prompt Engineering
- Distributed Systems | High Availability | Fault Tolerance
- API Design | REST, GraphQL, gRPC | WebSocket Real-time Communication
A.I.Z.E.N - Multi-Agent RAG Orchestration System
Production-grade intelligent document processing system with advanced agent coordination
Architecture Highlights:
- Multi-agent orchestration using LangChain with custom coordination patterns
- Hybrid retrieval system combining dense and sparse vectors for optimal accuracy
- Distributed task queue with Redis for horizontal scaling
- Real-time streaming responses via WebSocket with backpressure handling
- Observability stack: Prometheus, Grafana, Jaeger for distributed tracing
Tech Stack: Python LangChain FastAPI PostgreSQL Redis Docker Kubernetes
Impact: Achieved 40% improvement in retrieval accuracy with sub-200ms latency at scale
G.A.L.A.C.T.U.S - Distributed AI Infrastructure
Fault-tolerant, horizontally scalable ML inference platform
Key Features:
- Dynamic model serving with A/B testing and canary deployments
- Auto-scaling based on custom metrics (latency, throughput, GPU utilization)
- Multi-region deployment with intelligent request routing
- Circuit breaker pattern for service resilience
Tech Stack: Kubernetes Istio TensorFlow Serving AWS EKS Terraform
I regularly write deep-dive technical articles on AI systems, distributed architectures, and software engineering:
- Building A.I.Z.E.N: A Production Multi-Agent RAG Orchestration System
- G.A.L.A.C.T.U.S:
- Demystifying GPT: A Deep Dive into the Architecture of Modern AI
- Unveiling the Duplicity of AI: The Hidden Threat of Backdoor Behaviors in Language Models
- Supercharging Your Terminal: The Sorcery of Zsh on macOS
Creating in-depth technical content on AI, system design, and software engineering:
Recent Videos:
- Multithreading is a LIE (use this instead)
- What Experts Are Hiding About AI's Future
- Why Everyone's Wrong About AI Taking Over Coding
- Agentic AI: The shift from assistant to autonomous actor
- How Hackers Stole 560 Million Records with One Stupid Cloud Mistake
Focus Areas: AI/ML Systems • Distributed Architecture • Cybersecurity • System Design
I'm interested in connecting with engineers working on:
- Advanced AI Systems - Multi-agent architectures, LLM orchestration, novel AI applications
- Distributed Systems - High-scale infrastructure, real-time systems, performance optimization
- Open Source - Contributing to impactful projects in AI/ML and cloud-native ecosystems
- Research - Applied ML research, system architecture patterns, AI safety
- 💼 Professional Networking → LinkedIn
- 📺 Technical Content → YouTube - Cyber Creed
- ✍️ Deep Dives & Articles → Medium
- 🌐 Portfolio & Case Studies → creatorghost.com
- 📫 Opportunities → Open to consulting, speaking engagements, and senior engineering roles
