Data & AI Engineer | Cloud-Native Builder | MLOps Professional

I build and share end-to-end data & AI solutions — from scalable ETL pipelines and ML models to RAG-powered LLM applications and cloud-native deployments. My focus is blending data engineering, AI research, and software craftsmanship to create systems that are both technically rigorous and impactful.

Many of the repositories here are learning projects and experiments — built to explore new tools, validate best practices, and demonstrate how advanced ideas (like Langflow, LLMs, MLOps, and cloud automation) translate into real-world implementations.

• 🛠️ Building enterprise-grade data pipelines with Python, SQL, Scala, and Apache Spark.
• 🧩 Designing RAG pipelines that combine structured + unstructured data with Langflow, Weaviate, and ChromaDB.
• 🤖 Developing with LLMs (Ollama, vLLM, LangChain, Triton) to solve real-world problems in healthcare, analytics, and automation.
• ⚡ Practicing MLOps with Airflow, MLflow, Ray, and Kubeflow for experimentation → deployment at scale.
• 🌐 Creating interactive apps with React, TypeScript, and FastAPI backends.
• ☁️ Architecting cloud-native solutions across AWS and GCP, with Terraform for IaC.
• 🐳 Containerizing and orchestrating workloads with Docker and Kubernetes.
• 🐹 Exploring Go for high-performance backend microservices.

• Data Engineering: Python, SQL, Scala, Apache Spark, Airflow, Kubeflow
• AI & LLMs: Langflow, LangChain, Ollama, Weaviate, ChromaDB, RAG pipelines
• MLOps & Distributed Training: MLflow, Ray, PyTorch, TensorFlow
• Databases: PostgreSQL, MySQL, MongoDB, SQLite
• Cloud Platforms: AWS, GCP (Terraform, Serverless, BigQuery, S3, Lambda)
• DevOps & Infra: Docker, Kubernetes, Terraform, CI/CD
• Backend & APIs: Go, FastAPI, Node.js
• Frontend: React, TypeScript, JavaScript, HTML/CSS
• Version Control: GitHub, Bitbucket, Gitea

• Advanced RAG Architectures — scaling retrieval pipelines with hybrid search and embeddings.
• Langflow Extensions — writing custom components to integrate private APIs into workflows.
• LLM Optimization — deploying high-throughput inference with vLLM and GPU clusters.
• Terraform + Cloud Security — FISMA/NIST-compliant multi-environment deployments.

• Clinical AI Agents — building safe pipelines for triage, EHR summarization, and decision support.
• Generative AI for Media — exploring Flux and Stable Diffusion for creativity and research.
• RAG at Scale — combining structured healthcare data with LLM retrieval systems.

• 📜 Earn AWS Certified Developer – Associate and GCP Associate Cloud Engineer.
• 🏗️ Build and release production-ready AI/data repos that show cloud + ML integration.
• 🤝 Contribute to open-source AI and MLOps projects.

⭐️ Follow me on GitHub for new LLM, RAG, and cloud-native AI engineering projects.

Python	Scala	Go	React	FastAPI
Docker	Kubernetes	Terraform	AWS	Azure
GCP	PostgreSQL	MySQL	MongoDB	Airflow
PyTorch	TensorFlow	MLflow	Ray	LangChain
Weaviate	ChromaDB	Langflow	GitHub	Git